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The Condition of 








Tidal Wetlands of Washington, 
Oregon, and California - 2002 






















EPA/620/R-07/002 
September 2007 



The Condition of Tidal Wetlands 
of Washington, Oregon, 
and California - 2002 


Authors 

Walter G. Nelson, Henry Lee II, Janet O. Lamberson, Faith A. Cole, 
Christine L. Weilhoefer and Patrick J. Clinton 


U.S. Environmental Protection Agency 
Office of Research and Development 
National Health and Environmental Effects Research Laboratory 

Western Ecology Division 
Newport, Oregon, 97365 



Disclaimer 


The information in this document has been funded wholly or in part by the U.S. 
Environmental Protection Agency under Cooperative Agreements with the State of 
Washington Department of Ecology (CR 827869 ), Oregon Department of 
Environmental Quality (CR 87840 ), and Southern California Coastal Water Research 
Project (CR 827870 ). It has been subjected to review by the National Health and 
Environmental Effects Research Laboratory and approved for publication. Approval 
does not signify that the contents reflect the views of the agency, nor does mention of 
trade names or commercial products constitute endorsement or recommendation for 
use. 



2009 416138 








Preface 


This document is one of a series of summaries for the U.S. Environmental Protection 
Agency (EPA), National Coastal Assessment West Coast regional component (NCA- 
West). The NCA is the coastal component of the nationwide Environmental Monitoring 
and Assessment Program (EMAP). This document is a summary of a pilot assessment 
of the condition of estuarine intertidal, soft bottom habitat of the states of Washington, 
Oregon and California. The NCA in the West Coast region is a collaborative effort 
between EPA and the states of Hawaii, Alaska, California, Oregon and Washington, the 
territories of Guam and American Samoa, and the National Oceanic and Atmospheric 
Administration (NOAA). The program is administered through the EPA and 
implemented through partnerships with a combination of federal and state agencies, 
universities and the private sector. The West Coast Estuarine Intertidal Assessment 
involved the participation and collaboration of EPA, Washington Dept, of Ecology, 
Oregon Dept, of Environmental Quality, and the Southern California Coastal Water 
Research Project (SCCWRP), with additional contributions from personnel of Moss 
Landing Marine Laboratories and the San Francisco Estuary Institute. 

The appropriate citation for this report is: 

Walter G. Nelson, Henry Lee II, Janet O. Lamberson, Faith A. Cole, Christine L. 
Weilhoefer, and Patrick J. Clinton. 2007. The Condition of Tidal Wetlands of 
Washington, Oregon and California - 2002. Office of Research and Development, 
National Health and Environmental Effects Research Laboratory, EPA/620/R-07/002. 


Acknowledgments 


The NCA-West involves the cooperation of a significant number of federal, state, 
and local agencies. The project has been principally funded by the U.S. Environmental 
Protection Agency, Office of Research and Development. 

Many individuals within EPA made important contributions to NCA-West. Critical 
guidance and vision in establishing this program were provided by Kevin Summers of 
Gulf Ecology Division. Tony Olsen of Western Ecology Division (WED) provided the 
sampling designs utilized for various aspects of the continental shelf study. Lorraine 
Edmond of Region 10 and Terrence Fleming of the Region 9 Offices of EPA ably served 
as the regional liaisons with the state participants. Robert Ozretich of WED performed a 
detailed review of the database contents used for this analysis, and we additionally 
thank him for his extensive quality assurance review of this document. 

All members of the three state field crews are commended for their high level of 
technical expertise, teamwork and dedication to getting the required sampling 
completed. Project wide information management support during initial phases of the 
intertidal sampling effort was provided by SCCWRP as part of their cooperative 
agreement, and later by Computer Sciences Corporation (CSC) personnel. 

Josh Collins provided leadership and direction for the field crews involved in the 
marsh habitat assessments in San Francisco Bay. The general assistance of the San 
Francisco Estuary Institute and its staff with the study are acknowledged. Martha 
Sutula of SCCWRP provided the leadership and direction for the field crews involved in 
the intertidal assessments in the Southern California region. Both individuals provided 
valuable insights into potential condition indicators, and were responsible for design and 
implementation of supplemental studies conducted in parallel in San Francisco Bay and 
Southern California. 

Laura Brophy of Green Point Consulting provided training on marsh plant 
identification to field crews in Oregon and Washington. 


IV 


Table of Contents 


Disclaimer.ii 

Preface.jjj 

Acknowledgments.iv 

List of Figures.viii 

List of Tables.xi 

List of Appendix Tables.xii 

List of Acronyms.xiii 

Executive Summary.xiv 

1.0 Introduction.1 

1.1 Program Background.1 

2.0 Methods.2 

2.1 Sampling Design.2 

2.2 Biological and Sediment Sampling.4 

2.2.1 Site Location.4 

2.2.2 Site Description - Station Occupation.5 

2.2.3 Plant Composition/Cover and Burrow Counts.5 

2.2.4 Surficial Sediment Sample.6 

2.2.5 Sediment Pollutant and Nutrient Analysis.6 

2.2.6 Benthic Infaunal Samples.6 

2.3 Shoreline Land Use.9 

2.4 Quality Assurance.9 


v 























2.4.1 Quality Assurance/ Quality Control of Chemical Analyses.9 

2.4.2 Metals in Sediments.10 

2.4.3 Organics in Sediments.10 

2.5 Data Analyses .12 

3.0. Results and Discussion.13 

3.1 Sampling Locations.13 

3.2 Sediment Quality.26 

3.2.1 Sediment Composition.26 

3.2.2 Sediment Total Organic Carbon.27 

3.2.3 Sediment Nutrients.28 

3.2.4 Sediment Contaminants.30 

3.3 Biological Condition.32 

3.3.1 Benthic Infauna.32 

3.3.2 Plant Community.43 

Quadrat Species Assemblages and Percent Cover.43 

Quadrat Emergent Macrophyte Height and Seagrass Maximum Length.45 

Quadrat Biomass.45 

Transect Species Assemblages and Percent Cover.46 

Summary of Vegetation Results.48 

3.4 Shoreline Land Use.56 

3.5 Lessons Learned.56 

3.6 Summary.58 

vi 
























4.0 Literature Cited.60 

5.0 Apendices.63 


VII 




List of Figures 


Figure 3.1.1. Views of field sampling activities during the 2002 NCA Intertidal 
Assessment in Oregon (A), Washington (B,D) and California (C).13 

Figure 3.1.2. Percentage area of habitat types for the 2002 West Coast Intertidal 
Assessment.14 

Figure 3.1.3. Distribution of sampling stations in Washington and Oregon for the 2002 
West Coast Intertidal Assessment.15 

Figure 3.1.4. Distribution of sampling stations in California for the 2002 West Coast 
Intertidal Assessment.16 

Figure 3.1.5. Distribution of sampling stations with station numbers in Puget Sound for 
the 2002 West Coast Intertidal Assessment.17 

Figure 3.1.6. Distribution of sampling stations with station numbers for the outer coastal 
estuaries of Washington for the 2002 West Coast Intertidal Assessment.18 

Figure 3.1.7. Distribution of sampling stations with station numbers for the northern half 
of Oregon for the 2002 West Coast Intertidal Assessment.19 

Figure 3.1.8. Distribution of sampling stations with station numbers for the southern half 
of Oregon for the 2002 West Coast Intertidal Assessment.20 

Figure 3.1.9. Distribution of sampling stations with station numbers for Coos Bay, 

Oregon for the 2002 West Coast Intertidal Assessment.21 

Figure 3.1.10. Distribution of sampling stations with station numbers for the northern 
half of California for the 2002 West Coast Intertidal Assessment.22 

Figure 3.1.11. Distribution of sampling stations with station numbers for the southern 
half of California for the 2002 West Coast Intertidal Assessment.23 

Figure 3.1.12. Distribution of sampling stations with station numbers for Areata and 
Humboldt Bays, California for the 2002 West Coast Intertidal Assessment.24 

Figure 3.1.13. Distribution of sampling stations with station numbers for San Francisco 
Bay, California for the 2002 West Coast Intertidal Assessment.25 

Figure 3.2.1. Percent fine sediments for the 2002 West Coast Intertidal Assessment. 26 


VIII 















Figure 3.2.2. Percent sediment total organic carbon (TOC) for the 2002 West Coast 
Intertidal Assessment.27 

Figure 3.2.3. Average percent sediment total nitrogen for intertidal samples obtained in 
2002 for the West Coast region, individual states, and San Francisco Bay.28 


Figure 3.2.4. Average percent sediment total phosphorus for intertidal samples 
obtained in 2002 for the West Coast region, individual states, and San Francisco Bay. 
.29 


Figure 3.2.5. Average Effects Range-Median Quotient (ERM-Q) values for sediment 
contaminant concentrations for intertidal samples obtained in 2002 for the West Coast 
region, individual states, and San Francisco Bay.31 

Figure 3.3.1. Average total benthic abundance for intertidal samples obtained in 2002 
for the West Coast region, individual states, and San Francisco Bay.40 

Figure 3.3.2. Taxonomic composition of the benthic fauna based on relative abundance 
of the taxa for intertidal samples obtained in 2002 for the West Coast region.40 

Figure 3.3.3. Percent of nonindigenous species relative to the number of 
nonindigenous and native species per sample (NISs PP ). Analysis based on all sites 
including the high marsh in San Francisco with the exception of three samples with no 
nonindigenous or native species (N = 214).41 

Figure 3.3.4. Average percent of nonindigenous species relative to the number of 
nonindigenous and native species per sample (NIS Spp ) by location for intertidal samples 
obtained in 2002.41 

Figure 3.3.5. Relative abundance of nonindigenous species relative to the number of 
nonindigenous and native species per sample (NISAbun)- Analysis based on all sites 
including the high marsh in San Francisco with the exception of three samples with no 


nonindigenous or native species (N = 214).42 

Figure 3.3.6. Average percent of nonindigenous species relative to the abundance of 
nonindigenous and native species per sample (NISAbun) by location for intertidal 
samples obtained in 2002.42 

Figure 3.3.7. Mean relative abundance of vegetation groups and bare area in 
vegetation quadrats.49 

Figure 3.3.8. Relative percent cover of Salicornia virginica in the vegetation quadrats 
at sites where present (mean ± 1 sd).49 


IX 














Figure 3.3.9. Relative percent cover of Zostera marina in the vegetation quadrats at 
sites where present (mean ± 1 sd).50 


Figure 3.3.10. Relative percent cover of Zostera japonica in the vegetation quadrats at 
sites where present (mean ± 1 sd).50 

Figure 3.3.11. Relative percent cover of green algae in the vegetation quadrats at sites 
where present (mean ± 1 sd).51 

Figure 3.3.12. Relative percent cover of nonindigenous species in the vegetation 
quadrats at sites where present (mean ± 1 sd).51 

Figure 3.3.13. Total vegetation (emergent macrophytes, seagrass, algae) biomass in 
the vegetation quadrats (mean ± 1 sd).52 

Figure 3.3.14. Mean proportion of quadrat biomass for each vegetation group.52 

Figure 3.3.15. Mean relative abundance of vegetation groups and bare area in 
vegetation transects.53 

Figure 3.3.16. Relative percent cover of Salicornia virginica in the vegetation transects 
at sites where present (mean ± 1 sd).53 

Figure 3.3.17. Relative percent cover of Zostera marina in the vegetation transects at 
sites where present (mean ± 1 sd).54 

Figure 3.3.18. Relative percent cover of Zostera japonica in the vegetation transects at 
sites where present (mean ± 1 sd).54 

Figure 3.3.19. Relative percent cover of green algae in the vegetation transects at sites 
where present (mean ± 1 sd).55 

Figure 3.3.20. Relative percent cover of nonindigenous species in the vegetation 
transects (mean ± 1 sd).55 

Figure 3.4.1. Percentage areas within assessment regions with shoreline adjacent to 
sample locations in different land use categories.56 


x 















List of Tables 


Table 2.1.1. Summary of the sampling design by state and multidensity category 


for the 2002 West Coast Intertidal Assessment.4 

Table 2.2.1. Compounds analyzed in all three states in sediments.8 


Table 3.3.1. Average abundance, percent frequency of occurrence, and maximum 
abundance of the fifty most abundant species in the West Coast Intertidal Assessment 
.37 


XI 





List of Appendix Tables 


Appendix Table 1.1. Summary of quality assurance results for sediment metals.63 

Appendix Table 1.2. Summary of quality assurance results for sediment PAHs.63 

Appendix Table 1.3. Summary of quality assurance results for sediment PCBs.64 

Appendix Table 1.4. Summary of quality assurance results for sediment DDTs and 

other chlorinated pesticides.64 

Appendix Table 2. Sampling coordinates for the 2002 West Coast Intertidal 
Assessment.65 

Appendix Table 3. Summary of sediment composition (percent fines), total organic 
carbon (TOC), total nitrogen (TN) and total phosphorus (TP) concentrations, and 
contaminant concentrations for all intertidal sites, including high marsh, sampled in 
2002.70 

Appendix Table 4. Vegetation type and number of sites present in vegetation quadrats 
and transects for all vegetation species encountered.76 

Appendix Table 5. Relative percent cover of vegetation taxa (mean and range at sites 
present) in quadrats.78 

Appendix Table 6. Quadrat maximum leaf length (cm) of vegetation taxa (mean and 
range at sites present.80 

Appendix Table 7. Quadrat biomass (g/m 2 ) of vegetation taxa (mean and range at sites 
present).81 


Appendix Table 8. Relative cover of vegetation taxa (mean and range at sites present) 
in transects.83 













List of Acronyms 


BEST 

CDF 

CRM 

CVAA 

CWA 

EMAP 

EPA 

ERL 

ERM 

GAO 

GCECD 

GCMS 

GIS 

ICPAES 

ICPMS 

LCM 

MDL 

NCA 

NCA-West 

NIS 

NOAA 

ORD 

PAH 

PCB 

QA/QC 

RL 

RPD 

SCCWRP 

SRM 

TOC 

WED 


Biomonitoring of Environmental Status and Trends Program 

Cumulative Distribution Function 

Certified Reference Material 

Cold Vapor Atomic Adsorption 

Clean Water Act 

Environmental Monitoring and Assessment Program 

U.S. Environmental Protection Agency 

Effects Range Low 

Effects Range Median 

U. S. General Accounting Office 

Gas Chromatography and Electron Capture Detection 

Gas Chromatography/Mass Spectroscopy 

Geographic Information System 

Inductively-Coupled Plasma Atomic Emission Spectrometer 
Inductively Coupled Plasma-Mass Spectrometry 
Laboratory Control Material 
Method Detection Limit 
National Coastal Assessment 

National Coastal Assessment - West Coast regional component 
Nonindigenous Species 

National Oceanic and Atmospheric Administration 

EPA Office of Research and Development 

Polycyclic Aromatic Hydrocarbons 

Polychlorinated Biphenyls 

Quality Assurance/Quality Control 

Reporting Limit 

Relative Percent Difference 

Southern California Water Resources Research Project 
Standard Reference Material 
Total Organic Carbon 
Western Ecology Division 


XIII 


Executive Summary 


An assessment of the condition of the intertidal, soft sediment habitat of the 
states of Washington, Oregon, and California was successfully conducted during the 
summer of 2002. The assessment survey was conducted under the EPA National 
Coastal Assessment Program (NCA), in partnership with Washington Department of 
Ecology, Oregon Department of Environmental Quality, and the Southern California 
Coastal Water Research Project (SCCWRP), with additional contributions from 
personnel of Moss Landing Marine Laboratories and the San Francisco Estuary 
Institute. 

A major impetus for conducting the intertidal assessment is the fact that on the 
West Coast, the large tidal amplitude experienced over much of the region means that a 
large proportion of total estuarine area is intertidal. Methods and indicators for 
assessment of condition in the NCA program were primarily developed for sampling of 
subtidal habitats within estuaries of the Atlantic and Gulf coasts. The western regional 
component of the NCA therefore needed to develop a variety of modified methods and 
additional indicators to be able to assess condition in the extensive estuarine intertidal 
zones prevalent in West Coast estuaries. Additional emphasis was placed on site 
characterization metrics that included the occurrence of macroalgal beds/mats, 
submerged aquatic vegetation (SAV) or emergent vegetation, the presence of 
burrowing shrimp, the occurrence of marine debris, and obvious evidence of disruptive 
anthropogenic activities (e.g., dredging or landfill activity). Measurements of sediment 
nutrients (total N, total P) were added as potential indicators of site eutrophication 
where water column samples could not be taken. Where plants (seagrass, marsh 
plants, macroalgae) were encountered, percent cover and biomass estimates to lowest 
feasible taxonomic level were obtained. For rooted plants, maximum plant height was 
measured. Categorization of shoreline land use adjacent to sample sites was included 
as a potential indicator of land use stressors on the intertidal sites. 

Data were successfully collected from a total of 217 out of 223 targeted sites in 
the intertidal zone of the three west coast states, with the exception of the estuarine 
zone of the Columbia River, which had been extensively sampled in previous NCA 
assessments. The definition of intertidal zone for the west-wide sampling included all 
intertidal area except that classified by the National Wetlands Inventory as hard 
substrate, high marsh, diked, or artificial substrate. The study utilized a stratified 
random sampling design, with sampling effort partitioned among states (Washington - 
68, Oregon - 65, California - 90), and among regions within a state. Washington sites 
were divided among Puget Sound (25), Willapa Bay (30), and the remaining estuaries 
(13). Oregon sites were divided between Coos Bay (30) and the remaining estuaries 
(35). The California sites were divided among pilot study areas in Southern California 
(30), San Francisco Bay (30), and the remaining estuaries (30). 

The San Francisco Bay pilot study differed from the remainder of the study by 
dividing sampling effort approximately equally between three habitat types, tide flats, 
low marsh, and high marsh (excluded elsewhere). For both the San Francisco and 


XIV 


Southern California pilot studies, a two stage randomization procedure was followed. 

As the first stage, wetland systems were randomly selected from a list of systems, and 
then a point sampling location was randomly selected within the selected wetland. 

The area of different estuarine intertidal habitats varied somewhat among the 
three states, although uniformly, either unvegetated sand or mud flats occupied the 
greatest percentage of estuarine area. Shellfish beds (oysters), gravel bottom, and 
intertidal seagrasses were recorded only in Washington and Oregon. San Francisco 
Bay and the rest of California tended to have finer sediments, higher Total Organic 
Carbon, and higher concentrations of sediment nitrogen and phosphorus than estuarine 
intertidal areas in Washington and Oregon. 

For sediment contaminants, there was a pattern of higher average Effects 
Range-Median Quotient (ERM-Q) within San Francisco Bay and the rest of California as 
compared with Washington and Oregon. All values of average ERM-Q for the five 
major areas in the present study were below guideline levels from other studies that 
have determined biotic effects associated with ERM-Q values. Levels of sediment 
contamination across the intertidal of the three western states were generally quite low, 
with only 0.21% of the intertidal area of the West Coast estuaries having exceedances 
of >5 Effects Range Low (ERL) concentrations, and only 0.3% of the intertidal area 
exceeding Effects Range Median (ERM) concentrations. In all cases, the exceedances 
of the ERMs were due to DDT and/or its congener 4,4’ DDE. Some caution in 
interpretation of sediment contaminant results is warranted. While analyses of sediment 
metals met QA requirements in all states, analyses of PAHs, PCBs, and some 
pesticides from Oregon did not generally meet analytical targets. 

Average densities of benthic infauna were highest in Oregon, with California and 
San Francisco having lower but similar abundances, and Washington having the lowest 
value. The benthic community was dominated by polychaetes, oligochaetes and 
amphipods. Surprisingly, the single most abundant polychaete in the West Coast 
intertidal was the nonindigenous Manayunkia aestuarina, introduced from the Northeast 
Atlantic. San Francisco habitats, other than the high marsh, were the most invaded, 
with an average of almost 50% of the classified species per sample consisting of 
nonindigenous species. Puget Sound samples contained about 26% nonindigenous 
species compared to 40% and 44% for coastal Oregon and Washington, respectively. 

Vegetation was present in the quadrats at 150 of the 217 sites successfully 
sampled, and included 28 emergent macrophytes, 2 seagrasses, as well as 
macroalgae. Eighty-two percent of plant taxa occurred at three or fewer sites. The 
most frequently occurring emergent macrophyte taxa were marsh jaumea ( Jaumea 
carnosa) and pickleweed ( Salicornia virginica). The greatest number of emergent 
macrophyte species were observed in California (n = 11), and in San Francisco Bay (n 
= 17) where high marsh was included in the study. Mean cover of nonindigenous, 
emergent macrophyte species was low (8%) throughout the West. Mean cover by 
nonindigenous species was highest in Washington (21%), where both salt marsh 
cordgrass Spartina alterniflora and the introduced seagrass Zostera japonica were 


xv 


found. No nonindigenous macrophyte species were observed at California sites, except 
one high marsh site in San Francisco Bay. 

Shoreline land use adjacent to sample sites showed much higher percentages of 
urban shoreline in California and San Francisco Bay than in Washington and Oregon. 
Much of the undeveloped land in the latter two states was in silviculture. Surprisingly, 
estimates of residential shoreline in the three states were relatively similar. 

The study showed that further refinements of measurement approaches for plant 
community and shoreline development indicators are needed. Quadrat and transect 
sizes selected for plant community assessment proved too small for effectively 
capturing plant diversity at sample sites. While it was believed that available habitat 
maps for the west coast were insufficiently accurate to establish marsh-type strata for 
the sampling design, this proved false, and partitioning of sampling effort by habitat 
across the region may have improved the assessment. Better guidance on shoreline 
development classification is required to reduce variance among field crews. In spite of 
the costs for processing benthic samples with high levels of organic materials, 
volumetric sub sampling is not recommended because of the problems produced in 
intercomparison of data among sites for benthic community metrics. 

The results of this assessment study represent the first regional scale survey of 
the condition of intertidal wetland habitats on the West Coast. Findings confirm results 
from previous National Coastal Assessment studies of West Coast estuaries that have 
shown that sediment contamination issues are limited in extent, but that West Coast 
estuaries have been broadly invaded by nonindigenous species. 


XVI 


1.0 Introduction 


1.1 Program Background 

Safeguarding the natural environment is fundamental to the mission of the U.S. 
Environmental Protection Agency (EPA). The legislative mandate to undertake this part 
of the Agency’s mission is embodied, in part, in the Clean Water Act (CWA). Sections of 
this Act require the states to report the condition of their aquatic resources and list those 
not meeting their designated use (Section 305b and 303d respectively). Calls for 
improvements in environmental monitoring date back to the late 1970’s, and have been 
recently reiterated by the U. S. General Accounting Office (U.S. GAO, 2000). The GAO 
report shows that problems with monitoring of aquatic resources continue to limit states’ 
abilities to carry out several key management and regulatory activities on water quality. 
At the national level, there is a clear need for coordinated monitoring of the nation’s 
ecological resources. As a response to these needs at state and national levels, the 
EPA Office of Research and Development (ORD) has undertaken research to support 
the Agency’s Regional Offices and the states in their efforts to meet the CWA reporting 
requirements. The Environmental Monitoring and Assessment Program (EMAP) is one 
of the key components of that research. The EMAP Western Pilot program was 
established as a regional research effort to develop and demonstrate the tools needed 
to measure ecological condition of the aquatic resources in the 14 western states in 
EPA Regions 8, 9, and 10. 

The coastal assessment component of the EMAP Western Pilot began as a 
partnership with the states of California, Oregon and Washington, the National Oceanic 
and Atmospheric Administration, and the Biomonitoring of Environmental Status and 
Trends Program (BEST) of the U.S. Geological Survey to measure the condition of the 
estuaries of these three states. Sampling began during the summer of 1999 and the 
initial phase of estuarine sampling was completed in 2000. Beginning in 2000, the 
Western Coastal Assessment efforts became integrated into the EPA National Coastal 
Assessment Program (NCA). 

The NCA is a multi-year effort led by EPA’s Office of Research and Development 
to evaluate the assessment methods it has developed to advance the science of 
ecosystem condition monitoring. This program has surveyed the condition of the 
Nation’s coastal resources (estuaries and offshore waters) by creating an integrated, 
comprehensive coastal monitoring program among the coastal states to assess coastal 
ecological condition. The NCA is accomplished through strategic partnerships with all 
24 U.S. coastal states. Using a compatible, probabilistic design and a common set of 
survey indicators, each state conducts the survey and assesses the condition of their 
coastal resources independently. Because of the compatible design, these estimates 
can be aggregated to assess conditions at the EPA Regional, biogeographical, and 
national levels. Data from this program provide the basis for individual reports of 
coastal conditions for each state (Nelson et al., 2004, 2005, 2007; Hayslip et al., 2006, 
Wilson and Partridge, 2007), as well as providing data for a series of National Coastal 
Condition Reports (U.S. EPA 2001,2004, 2006). 


1 


On the West Coast, the large tidal amplitude experienced over much of the 
region means that a large proportion of total estuarine area is intertidal. For example, 
intertidal habitat constitutes 52% of the estuarine area averaged over all Pacific 
Northwest estuaries, and can constitute as much as 90% in some systems (e.g., Netarts 
Bay; Lee et al., 2006). The initial development of methods and indicators for 
assessment of condition in the NCA were for sampling of subtidal habitats within 
estuaries of the Atlantic and Gulf coasts. Because the Western component of the NCA 
began as a pilot program, there was an opportunity to test development of a variety of 
modified methods and additional indicators for assessment of condition in the extensive 
estuarine intertidal zones prevalent in West Coast estuaries. 

Therefore a pilot assessment of the intertidal habitat of the states of Washington, 
Oregon, and California was carried out in the summer of 2002. This report provides a 
technical summary of the data from this assessment. 


2.0 Methods 

Methods for the 2002 intertidal survey were in general the same as those 
developed for the EPA National Coastal Assessment (Nelson et al., 1999), with 
modifications to reflect the intertidal nature of the resource being assessed. Because 
of the intertidal focus of the survey, water quality and fish tissue samples were omitted 
while vegetational-quadrat and transect samples were added. 

2.1 Sampling Design 

The target resource assessed was the intertidal zone of the states of 
Washington, Oregon and California, with the exception of the estuarine portion of the 
Columbia River. The Columbia was extensively sampled by EMAP surveys conducted 
in 1999, 2000, and 2001, and additional sampling was deemed to be redundant. 

The sample frame is a map defining the target resource. The principal map 
coverage used to develop the 2002 intertidal GIS data layer that was the sample frame 
was the National Wetlands Inventory (NWI) in Arclnfo format. An Arclnfo coverage of 
San Francisco Bay baylands, created by the San Francisco Estuary Institute (SFEI), 
was selected as the map source in the San Francisco Bay area. In some cases, digital 
coverage was lacking, and hard copy maps were scanned and georeferenced, and 
estuarine polygons were hand digitized. 

In order for a polygon to be included in the sample frame coverage for all areas 
except San Francisco Bay (see below), the polygon had to have the following attributes: 
it had to be classified as intertidal, and not classified as hard substrate, high marsh, 
diked, or artificial substrate. Several codes within the NWI coverages were interpreted 
as follows: ‘irregularly exposed’ was interpreted as below Mean Lower Water, and 


2 


‘irregularly flooded’ was interpreted as above Mean Higher Water. Both categories 
were excluded from the frame. 

The study utilized a stratified random sampling design. Within Washington, 
sampling effort was distributed such that Puget Sound received 25 stations, there was 
an intensification of effort in Willapa Bay for a total of 30 stations, and the remaining 
estuaries of the state received 13 stations, for a total of 68 stations. In Oregon, there 
was an intensification of sampling in Coos Bay (30 stations), while 35 stations were 
located within the remaining estuaries of the state, for a total of 65 stations. 

The study design in California was more complex. Two pilot study areas were 
defined, Southern California (Point Conception to the Mexican border) and San 
Francisco Bay (downstream of the delta), each of which had 30 sampling stations. An 
additional 30 sites were randomly allocated along the California coastline outside of 
these intensification areas, for a total of 90 sites. The San Francisco Bay study area 
differed from the remainder of the study by dividing sampling effort approximately 
equally between three habitat types, tide flats, low marsh, and high marsh, with high 
marsh being a habitat type excluded from the remainder of the West Coast intertidal 
sampling frame. For both the San Francisco and Southern California pilot study areas, 
a two stage randomization procedure was followed. As the first stage, wetland systems 
were randomly selected from a list of systems, and then a point sampling location was 
randomly selected within the selected wetland. The advantage of this approach is that it 
allows condition estimates based on percentage of systems, while at the same time also 
allowing for the areal extent estimates of condition being used for all other geographic 
components of the intertidal survey. Wetlands systems are typically managed as 
discrete units rather than as continuous resources, and the two level randomization 
design provides the potential to report on the percentage of wetland systems that are 
meeting their management goals. 

Each sampling region is termed a multidensity category. For each multidensity 
category (see Appendix Table 1), geographic coordinates for the number of primary 
target stations described above were determined during the study design process. 
Additionally, each multidensity category except for the California pilot studies had 
random coordinates for nine times the number of primary stations selected as alternate 
sampling locations. The two California pilot studies had 1.5 times the number of 
primary sites selected to serve as alternate locations. Alternate locations would be 
sampled in the event a primary site was rejected for any reason, such as safety 
concerns or access issues. 


3 


Table 2.1.1. Summary of the sampling design by state and multidensity category for the 
2002 West Coast Intertidal Assessment. 


State 

Multidensity 

Category 

(Label) 

Design 
Target 
Number of 
Primary 
Sample 
Sites 

Design 
Actual 
No. of 
Sites 

No. Sites 
Successfully 
Sampled 

Number of 
Alternate 
Sample 
Sites 

Washington 

Puget Sound (Puget) 

25 

26 

24 

225 

Washington 

Willapa Bay (Willa) 

30 

30 

30 

271 

Washington 

Rest of State (Washi) 

13 

12 

7 

116 

Oregon 

Coos Bay (Coosb) 

30 

29 

30 

271 

Oregon 

Rest of State (Orego) 

35 

36 

36 

314 

California 

Rest of State (Calif) 

30 

29 

30 

271 

California 

San Francisco Bay 

Low Marsh (SF Low 
Marsh) 

10 

11 

9 

89 

California 

San Francisco Bay 

High Marsh (SF High 
Marsh) 

10 

10 

12 

91 

California 

San Francisco Bay Flat 
(SF Flat) 

10 

9 

9 

90 

California 

Southern California 
(Bight) 

30 

30 

30 

269 


2.2 Biological and Sediment Sampling 

Field sampling was performed independently by each state during a seasonal 
window spanning the period from July to mid-September. Intertidal sites were 
accessed, as appropriate, either by boat, hovercraft or on foot, at low tide to facilitate 
burrow counts, plant community, sediment chemistry and benthic community sampling. 
The core field data or sample types collected at each site included: 

- general habitat-type description and anthropogenic debris or perturbation 

- shoreline development 

- presence and cover of burrowing shrimp and other megafauna. 

- plant community composition and cover 

- sediment consistency, composition, salinity and temperature 

- sediment pollutants, including organics and trace metals; total organic carbon 

- sediment nitrogen and phosphate concentrations 

- benthic macroinvertebrate community structure 

2.2.1 Site Location 

The randomly selected sampling locations for each state were provided to the 
field crews, who located the sites by use of Global Positioning Satellite System (GPS). 


4 




















Because EMAP's probabilistic sampling design is unbiased, potentially, some of the 
generated sites can fall in locations that are not amenable to sampling (e.g., outside the 
sampling frame, danger or risk to crew, excessive rocky bottom, currents, man-made 
obstructions, etc.). Field teams had a limited degree of onsite flexibility to randomly 
relocate sampling sites when confronted with unexpected obstacles or impediments, but 
the new site was to be no further than 100 m and preferably 40 m from the original 
designated site. Alternative sample sites determined during the initial design process 
were used if a site was found to be unsuitable. 

2.2.2 Site Description - Station Occupation 

Observations were made in the field to document certain attributes or conditions 
to help characterize the overall ecological condition of the site. These included the 
occurrence of macroalgal beds/mats, submerged aquatic vegetation (SAV), or emergent 
vegetation, the presence of burrowing shrimp, the occurrence of marine debris, and 
obvious evidence of disruptive anthropogenic activities (e.g., dredging or landfill 
activity). 

Upon arrival at the sample site, the station number, GPS location, date, time, 
samplers’ initials and agency were recorded. If the station was abandoned, the reason 
for abandonment was also recorded. Observations were made on sea state, weather, 
wind speed and direction, and estimated tidal level as well as air temperature and 
habitat type. Three to five photos and notes were taken to document site characteristics 
and anthropogenic impact such as shoreline construction, dredging or recreational use. 
Habitat was defined by the presence or absence of factors such as dominant plant (e.g., 
Spartina sp., Zostera marina or Z. japonica) or animal (e.g. burrowing shrimp, or 
oysters) species that affect the abundance and number of species in the benthic 
infaunal community. The habitat was also defined by its geological type - rocky, gravel, 
coarse or fine sand, muddy sand, sandy mud or mud. 

2.2.3 Plant Composition/Cover and Burrow Counts 

A 0.25-m 2 quadrat was randomly placed at the GPS-located site and then turned 
over three times to define a 1-m square sampling site. The four adjacent 0.25-m 2 
quadrats were used for: 1) burrow counts; 2) plant cover; 3) sediment chemistry 
samples; and 4) benthic samples. The number of burrow holes of burrowing shrimp 
(Neotrypaea californiensis, Upogebia pugettensis) was counted in one of the 0.25-m 2 
quadrats at each site. If vegetation covered >50% of the quadrat, the vegetation was 
gently pulled back taking care to disturb the sediment surface as little as possible, and 
the density of burrow holes under the vegetation was visually estimated. 

Where rooted plants (e.g. seagrasses, marsh plants, Spartina) or macroalgae 
were present, the plant community was quantified in one of the 0.25-m 2 quadrats. 
Percent plant cover within the 0.25-m 2 quadrat was visually estimated separately for 
green, brown or red macroalgae, Zostera spp., Spartina or other rooted plant genera 
present, and bare (i.e., open, unvegetated) substrate. The maximum total cover 
possible for all species of plants in a quadrat is 100% times the number of species of 
plants in the plot, and thus may be greater than 100% if several species overlapped at 


5 


different layers of cover. For rooted species, the blade length of the longest blades was 
measured. The total biomass of each species of rooted plants and each type of algae in 
the quadrat was determined by cutting all vegetation at the sediment surface, sorting by 
species, and obtaining the dry weight (g dry weight) of biomass for each species. 

Plants were dried in the laboratory until they reached constant dry weight at 80 C. Plant 
composition and cover were also estimated using 25 random points along a 5-meter 
transect. Each plant species or open ground noted at the 25 random points along the 
5-m transect was recorded, with the possibility of more than one plant species occurring 
at each point. In all cases, seagrasses and other rooted plants were identified to 
species if possible, or to the lowest practical taxonomic level. If the species of plant was 
not known with certainty by the field crew, a reference specimen was taken by the field 
crew for identification by a qualified plant taxonomist. 

2.2.4 Surficial Sediment Sample 

At each site, surficial sediment layer (top 2-3 cm) was collected by spatula or 
scoop from one of the 0.25-m 2 quadrats to provide sediment for the analyses of 
inorganic and organic chemical contaminants, total organic carbon (TOC), and grain 
size determinations. Surficial sediment was combined in a clean, high-grade stainless 
steel or Teflon vessel and composited by stirring well to ensure a homogenous sample 
before sub-samples for the various analyses were taken (Table 2.2.1). 

2.2.5 Sediment Pollutant and Nutrient Analysis 

Sediment collected from each site was analyzed for a suite of organic pollutants, 
metals and interstitial nutrients (Table 2.2.1). Fifteen metals were analyzed in all three 
states. California quantified sediment metals including mercury using inductively 
coupled plasma mass spectrometry (ICPMS). Washington quantified all metals except 
mercury using ICPMS, and used cold vapor atomic absorption (CVAA) for mercury. 
Oregon quantified all metals except mercury using inductively coupled plasma atomic 
emission spectrophotometry (ICPAES) and CVAA for mercury. For organic pollutants, a 
total of 21 PCB congeners (PCBs), DDT and its primary metabolites, and 14 chlorinated 
pesticides were measured. There were 21 polycyclic aromatic hydrocarbons (PAHs) 
measured by all three states out of the 23 target compounds (Table 2.2.1); 
phenanthrene and dibenzothiophene were not measured by all three states. California 
and Washington used GCMS to quantify the PCBs, DDTs, pesticides, and PAHs. 

Oregon used GCECD for the chlorinated compounds and GCMS for the PAHs. 

California quantified total nitrogen using EPA method 415.1 while Oregon and 
Washington used CHN analyzers. All three states used ICPAES to quantify total 
sediment phosphorus. Total organic carbon (TOC) was analyzed in Washington by 
combustion and CHN analyzers while California and Oregon used CHN analyzers. 

2.2.6 Benthic Infaunal Samples 

The objective was to collect a 0.1-m 2 benthic infaunal sample to a depth of 10 cm 
at all sites, with the sample processed through a 1.0 mm mesh sieve. A specially 
designed post-hole corer sampler was constructed to assist in obtaining these intertidal 
benthic samples, though other sampling methods were acceptable if they had the same 
nominal area as the post-hole sampler. During the course of the survey, however, it 


6 


was discovered that the internal area of the post-hole corer was 0.09 m 2 but not before 
twelve samples were taken with other methods that had an actual area of 0.1 m 2 . 
Additionally, the volume of residue retained on the 1.0 mesh sieve at several sites 
exceeded several liters, which was impractical to process. This volume of residue 
necessitated sub-sampling the residue in 78 of the 217 samples (36%). The samples 
were subsampled to the minimum practical extent. The occurrence of 0.1 -m 2 samples 
and the subsampling resulted in twelve functional sample sizes, ranging from 0.0028 to 
0.1 m 2 , a 36-fold difference in sample area. Because the majority (56%) of the 
samples were taken with the post-hole sampler, all benthic abundances were 
normalized to 0.09 m 2 for analysis. Species richness does not scale linearly with area 
so no attempt was made to normalize the number of taxa per sample. Accordingly, we 
did not analyze species richness with the entire benthic data set. 


7 


Table 2.2.1. Compounds analyzed in all three states in sediments. 


Polyaromatic 

Hydrocarbons 

(PAHs) 

PCB Congeners 
(Congener Number and 
Compound) 

DDT and Other 
Chlorinated 
Pesticides 

Metals and 
Misc. 

Low Molecular Weight PAHs 

8: 2,4'-dichlorobiphenyl 

DDTs 

Metals 

1 -methylnaphthalene 

18: 2,2',5-trichlorobiphenyl 

2,4’-DDD 

Aluminum 

1 -methylphenanthrene 

28: 2,4,4'-trichlorobiphenyl 

4,4’-DDD 

Antimony 

2-methylnaphthalene 

44: 2,2',3,5'-tetrachlorobiphenyl 

2,4-DDE 

Arsenic 

2,6-dimethylnaphthalene 

52: 2,2',5,5'-tetrachlorobiphenyl 

4,4’-DDE 

Cadmium 

2,3,5-trimethylnaphthalene 

66: 2,3',4,4'-tetrachlorobiphenyl 

2,4’-DDT 

Chromium 

Acenaphthene 

77: 3,3',4,4'-tetrachlorobiphenyl 

4,4’-DDT 

Copper 

Acenaphthylene 

101: 2,2',4,5,5'-pentachlorobiphenyl 


Iron 

Anthracene 

105: 2,3,3',4,4'-pentachlorobiphenyl 

Cvclooentadienes 

Lead 

Biphenyl 

110: 2,3,3',4',6-pentachlorobiphenyl 

Aldrin 

Manganese 

Fluorene 

118: 2,3',4,4',5-pentachlorobiphenyl 

Dieldrin 

Mercury 

Naphthalene 

126: 3,3',4,4’,5-pentachlorobiphenyl 

128: 2,2',3,3',4,4'-hexachlorobiphenyl 

Endrin 

Nickel 

Selenium 

High Molecular Weight PAHs 

138: 2,2',3,4,4',5'-hexachlorobiphenyl 

Chlordanes 

Silver 

Benz(a)anthracene 

153: 2,2',4,4',5,5'-hexachlorobiphenyl 

Alpha-Chlordane 

Tin 

Benzo(a)pyrene 

170: 2,2',3,3’,4,4',5-heptachlorobiphenyl 

Heptachlor 

Zinc 

Benzo(b)fluoranthene 

180: 2,2',3,4,4',5,5'-heptachlorobiphenyl 

Heptachlor Epoxide 


Benzo(k)fluoranthene 

187: 2,2',3,4',5,5',6-heptachlorobiphenyl 

Trans-Nonachlor 


Benzo(g,h,i)perylene 

195: 2,2',3,3',4.4',5,6-octachlorobiphenyl 


Miscellaneous 

Chrysene 

206: 2,2',3,3',4,4',5,5',6-nonachlorobiphenyl 

Others 

Total Organic 

Dibenz(a,h)anthracene 

209: 2,2'3,3',4,4',5,5',6,6 '-decachlorobiphenyl 

Endosulfan 1 

Carbon 

Fluoranthene 


Endosulfan II 

Total Nitrogen 

Indeno( 1,2,3-c,d)pyrene 


Endosulfan Sulfate 

Total Phosphorus 

Pyrene 


Hexachlorobenzene 
Lindane (gamma-BHC) 
Mi rex 

Toxaphene 

Percent Fines 


8 















2.3 Shoreline Land Use 


Research has indicated that there tend to be relationships between land use or 
land cover types and indicators of estuarine condition. Both Comeleo et al. (1996) and 
Rodriguez et al. (2007) found significant associations between levels of urban land use 
and sediment contaminants in east coast estuaries. Generally such analyses require 
considerable effort in generating GIS coverages with associated land uses around the 
sampling points. The 2002 EMAP intertidal study included a pilot indicator of adjacent 
land use which was determined by the field crews at the time of the sample site visit. 
Crews provided a qualitative assessment of the dominant land use aspect for the 
shoreline most immediately adjacent to the sampling station by selecting a category 
from a list of land use types. Land use type was supplemented by additional 
descriptions in the form of comments and digital photos. Categories included 
agriculture, armored, commercial, highway, industrial, undeveloped, residential, urban, 
sanctuary, natural area, recreational, and fisheries uses. Several categories were 
combined in the final analysis with commercial being combined with industrial, and 
natural area plus sanctuary being combined with undeveloped. Fisheries use was only 
designated in Oregon and was relabeled oyster aquaculture to reflect the specific use 
noted. 

2.4 Quality Assurance 

2.4.1 Quality Assurance/ Quality Control of Chemical Analyses 

The quality assurance/quality control (QA/QC) program for the National Coastal 
Assessment - West program is defined by the “Environmental Monitoring and 
Assessment Program (EMAP): National Coastal Assessment Quality Assurance Project 
Plan 2001-2004" (U.S. EPA, 2001). A performance-based approach is used, which 
depending upon the compound includes 1) continuous laboratory evaluation through the 
use of Certified Reference Materials (CRMs), Laboratory Control Materials (LCMs), or 
Standard Reference Material (SRM); 2) laboratory spiked sample matrices, 3) 
laboratory reagent blanks, 4) calibration standards, 5) analytical surrogates, and 6) 
laboratory and field replicates. 

One measure of accuracy is “relative accuracy” which is based on comparing the 
laboratory’s value to the true or “accepted” values in CRMs or LCMs. The requirements 
for PAHs, PCBs, and pesticides are that the “Lab’s value should be within ±30% of true 
value on average for all analytes; not to exceed ±35% of true value for more than 30% 
of individual analytes” (U.S. EPA 2001). For metals and other inorganic compounds, 
the laboratory's value for each analyte should be within ±20% of the true value of the 
CRM, LCM, or SRM. Another measure of accuracy is the percent recovery from matrix 
spikes. High percent recoveries indicate that the analytical method and instruments can 
adequately quantify the analyte but do not evaluate the ability to actually extract the 
compound from tissue or sediment. Measures of precision are the “relative percent 
differences” (RPD) or coefficient of variation (CV) of duplicate samples, with the 
objective that the RPD or CV should be <30%. 


9 


A measure of whether the analytical procedure is sufficient to detect the analytes 
at environmental levels of concern is the Method Detection Limits (MDLs). Approved 
laboratories were expected to perform in general accord with the target MDLs presented 
for NCA analytes (Table A7-2 in U.S. EPA, 2001). Because of analytical uncertainties 
close to the MDL, there is greater confidence with concentrations above the Reporting 
Limit (RL), which is the concentration of a substance in a matrix that can be reliably 
quantified during routine laboratory operations. Typically, RLs are 3 to 5 times the MDL. 
In these analyses, concentrations between the MDL and the RL were included in the 
generation of mean values for the analyte, while any values below the MDL were set to 
0 . 


A post-analysis assessment of the success of the analytical laboratories in 
meeting NCA QA/QC requirements was conducted by the QA manager of the Western 
Ecology Division, which is summarized here. 

2.4.2 Metals in Sediments 

The analytical methods for metals by the three states are those used in the 
NOAA NS&T Program (Lauenstein and Cantillo, 1993) or documented in the EMAP 
Laboratory Methods Manual (U.S. EPA, 1994). The recommended MDL (Table A7-2 in 
U.S. EPA, 2001) varies by metal, ranging from 0.01 pg/g for mercury to 1500 pg/g for 
aluminum. All three states met the MDL requirements for all the metals. The percent 
recovery from certified/standard materials, recovery from matrix spikes, and the average 
RPD for non-zero sample duplicates and matrix spikes for the sediment metals are 
summarized in Appendix Table 1.1. All three states met all the overall quality 
assurance requirements for metals. While Oregon met the overall requirements, the 
relative accuracy for chromium, nickel, and tin ranged from 22% to 41% compared to 
the requirement of 20% for metals. 

2.4.3 Organics in Sediments 

As with the metals, the analytical methods for organic compounds are those used 
in the NOAA NS&T Program (Lauenstein and Cantillo, 1993) or documented in the 
EMAP Laboratory Methods Manual (U.S. EPA, 1994). The recommended MDL (Table 
A7-2 in U.S. EPA, 2001) is 10 ng/g for PAH compounds and 1 ng/g for the PCBs, DDTs, 
and chlorinated pesticides. All three states met the MDL requirements for all the 
organic compounds. 

The percent recovery from certified/standard materials, recovery from matrix 
spikes, and the average RPD for non-zero sample duplicates and matrix spikes for the 
sediment PAHs are summarized in Appendix Table 1.2. California met the 
requirements for the percent deviation from reference materials but slightly exceeded 
the RPD requirement among duplicate samples (33% vs. 30%). Washington slightly 
exceeded the requirement for the average deviation from reference materials (32% vs. 
30%) but met the requirements for the number of PAH analytes within +35% of the true 
value as well as the requirements for percent recovery from spiked sediment and the 
RPD of duplicates. While failing some of the requirements, the differences were 


10 


relatively small, indicating that the total PAH data from both Washington and California 
can be used quantitatively. The Oregon results are more problematic, as they had a 
greater difference between the measured and true values (43% vs. requirement of 30%) 
and 47% of the PAH analytes deviated by more than +35% from the true value. Also, for 
13 of the 22 PAH compounds, the CV from the replicate reference samples was >30%. 
Because of these deviations with both accuracy and precision, the total PAH data from 
Oregon needs to be interpreted cautiously. 

The QA results for sediment PCBs are summarized in Appendix Table 1.3. 
California met the requirements of deviation from the reference materials and the 
percent recovery of the matrix spikes. California did not have any duplicate non-zero 
reference values so it is not possible to evaluate this measure of precision. Washington 
slightly exceeded the requirements for the average deviation from reference materials 
(32% vs. 30%) and the percentage of analytes within +35% of the true value (67% vs. 
70%). Washington did meet the requirements for the percent recovery of matrix spikes 
and the RFP for duplicate samples. Because of these deviations, the Washington PCB 
results should be used with qualified caution. As with the PAHs, the PCB results for 
Oregon are problematic. The deviation from reference materials was 146% and only 
38% of the PCB congeners were within +35% of the true value. Because of the 
problems with accuracy, the total PCB data are best used qualitatively to identify 
locations with sediment PCBs. The subset of congeners that met the requirements for 
both accuracy and precision (PCB 28, 105, 110, 118, and 153) can be used to quantify 
differences in PCB concentrations among sites. 

The QA results for sediment DDTs and other chlorinated pesticides are 
summarized in Appendix Table 1.4. For California, LCMs were only analyzed for two of 
the DDT compounds (4,4’-DDD and 4,4-DDE) though all the pesticides were analyzed 
using recovery from spiked sediments. In the absence of certified pesticide 
concentrations in a sediment matrix with the complete suite of pesticides, the excellent 
recovery of matrix spiked pesticides will have to suffice as indirect evidence that the 
methods employed by California yield results that meet the requirements for accuracy. 
Washington met all the requirements for the chlorinated pesticides (Appendix Table 1.4) 
though several of the individual pesticides showed deviations of up to 72% in the spiked 
blanks. Because of these deviations with the spiked blanks, the Washington pesticide 
data should be used with qualified caution. Oregon had problems with the analytical 
surrogate coeluting with hexachlorobenzene (HCB), which resulted in a large average 
deviation from the reference material (127%). Excluding HCB reduced the average 
extent of deviation from the reference material (57%) but it still did not meet the QA 
requirement of 30%, although three DDT compounds (2,4’-DDD, 4,4’-DDD, and 4,4’- 
DDE) and alpha-chlordane were quantified within 35% of the reference values. Overall, 
the poor performance with the reference materials indicates that the Oregon pesticide 
results are best used qualitatively to identify locations with sediment pesticides, with the 
exception of the four compounds that quantified within 35% of the reference 
concentrations. 


11 


2.5 Data Analyses 

The use of a probability based sampling design allows the development of 
estimates of the extent of area, with 95% confidence intervals, of the intertidal resource 
that has any given observed indicator value. Analysis of indicator data was conducted 
by calculation of cumulative distribution functions (CDFs), an analysis approach that has 
been used extensively in other EMAP/NCA coastal studies (Summers et al. 1993, 
Strobel et al. 1995, Hyland et al. 1996, U.S. EPA 2004, 2006). A detailed discussion of 
methods for calculation of the CDFs used in EMAP analyses are provided in Diaz- 
Ramos et al. (1996). 

Data are presented in this report in several graphical forms. Comparisons 
among the three states Washington, Oregon, and California, the intensive study in San 
Francisco Bay, and the values for the entire Western intertidal region (omitting the high 
marsh samples from San Francisco Bay), are presented as bar charts of average 
values for the five categories plus 1 standard deviation as an estimate of error. Where 
there existed reasonable benchmarks to assign condition assessments to an indicator, 
estimates of the percentage area of the intertidal zone within the condition levels is 
provided in the text. 


12 


3.0. Results and Discussion 


3.1 Sampling Locations 

Samples were obtained from 217 stations located in the states of Washington, 
Oregon, and California ((Figs. 3.1.1- 3.1.13). Abbreviated station numbers are provided 
on Figs. 3.1.5-3.1.13, and complete station identification numbers, together with latitude 
and longitudes for sampling locations are given in Appendix Table 2. All stations were 
sampled during low tide, and most sites were completely exposed at the time of 
sampling. 



Figure 3.1.1. Views of field sampling activities during the 2002 NCA Intertidal 
Assessment in Oregon (A), Washington (B,D) and California (C). 


13 





















The substrate type varied widely and included salt marsh, oysters, and sand and 
mud flats (Fig. 3.1.2.). Percentage of area within the West Coast intertidal region 
sampled was statistically estimated for 9 habitat categories. The dominant types of 
estuarine intertidal habitat varied among the three states. Unvegetated tide flats, 
classified either as sand or mud flats, were the dominant habitat types for all three 
states, for San Francisco Bay, and for the west as a whole (Fig. 3.1.2.). Higher 
percentages of mud flats were recorded in California and San Francisco Bay versus 
Washington and Oregon, which possessed higher percentages of sand flats. Shellfish 
beds (oysters), gravel bottom, and intertidal seagrasses were recorded only in 
Washington and Oregon. The non-native marsh grass Spartina alterniflora was 
recorded in Washington in Willapa Bay, where efforts to eradicate the species are 
currently underway. 



Bank 

I I Gravel 

V////A High marsh 
l l Marsh 

SAV 

Tidal flat-Spartina 
I I Shellfish 

Z///A Tidal flat-mud 
k yyn Tidal flat-sand 


Figure 3.1.2. Percentage area of habitat types for the 2002 West Coast Intertidal 
Assessment. Values for California do not include San Francisco Bay. 


14 
















































o 

sc 



c 


0 





*r 



124°0'0"W 122°0'0"W 


Figure 3.1.3. Distribution of sampling stations in Washington and Oregon for the 2002 
West Coast Intertidal Assessment. 


15 











> 


a? 


Elk River A 


Chetco River 
Smith River (CA) A 


Oregon 


Big Lagoon 

Areata Bay 
Humboldt Bay 




Zj 

ZJ 



Bodega Bay ^ * 

Drakes Bay 

S'<i/r Francisco Bay *X Fl nnciseo 

Santa Cm: Harbor 

Elkhorn Slough A 
Carmel Bay 

Big Sur River 


California 


Morro Bay A 
San Luis Obispo Bay 


^ ■ 




Ventura Harbor 


•Los Angeles 


Los A)tgeles Harbor A.. 
Newport Bay ™ 
Point Harbor 



-1- 

124 C 0'0’'W 


-1- 

122°0 , 0' , n 


Mission Bay 
San Diego Bay 
Tijuana River 


if 

A 


-r 



118°0'<TJV 


Figure 3.1.4. Distribution of sampling stations in California for the 2002 West Coast 
Intertidal Assessment. 


16 














3 = 


4e 

> 




> 



n3°0'0"n 


122°30'0"n 


Figure 3.1.5. Distribution of sampling stations with station numbers in Puget Sound for 
the 2002 West Coast Intertidal Assessment. 


17 
















Pacific Ocean 


Q 

K 

> 


»#-. - 


O 

>c 


w 




037 


021 

▲ 


041 025 


00 ? 


026 


Grays 

Harbor 


045 


Washington 


078 

061 n-n A A05 ° 

A “V 18 


143a 
A 051 


019 


043 


035 


Oil 


087 


Willapa 

Bar 


a 067 102 

A 002 

▲ 


070 


123 


007A 


023 


027 127 


039 


003 


075A 

A 


‘ ▲ 

059 A 091 


049 


017 


065A 


0 

5 

10 

2?bm 



-1- 

124°0'0"W 


066 


> Rr.i 


-r 

12P45'0"W 


Figure 3.1.6. Distribution of sampling stations with station numbers for the outer coastal 
estuaries of Washington for the 2002 West Coast Intertidal Assessment. 


18 






o 

>o 


w 


Nr 

s 


p 

if. 


O 




3= 

T 


o 

3 


Xecanicum River 


▲66 


Xehalem River 


▲01 


49 


05 


Tillamook Bay 


41 4Ka 


Net am Bay 


.15 
47 4l3 
#53 


,▲45 


Xestucca Bay 


29 


▲68 


▲61 


Siletz Bay 


03 

435 


23 

Yaquitia Bay 

07jl39 


r» 27 


Alsea Bay 


'ik59 

±43 


ftl* 


ACrtv* 


ciS. 


XortA For* Trask ft w 


Oregon 


Anickreull Creek 






0 5 10 20 30 


40 
I ir»i 


124°30'0"W 


124 C 0'0"H' 


123°30'0"W 


Figure 3.1.7. Distribution of sampling stations with station numbers for the northern half 
of Oregon for the 2002 West Coast Intertidal Assessment. 


19 







3 s 

~T 


Sin slaw River 


51 


11 


W - E 


A v 


32 

64^52 12 

A* A 


Umpqua River 




Vi 

A 


Coos Bar 


Coqnille River 


48 


Sixes River 


31 


?o<ta Oregon 


34 

A 

73 


14 18 * 4^5 

A 

26 

58^ 

42 46 2° 


28 

A 


44 

A 


-1- 

124°30'0"W 


S 10 


20 


30 


-1- 

124°0'0"W 


Figure 3.1.8. Distribution of sampling stations with station numbers for the southern half 
of Oregon for the 2002 West Coast Intertidal Assessment. 


20 








43°l5'0 n <V 43°.W9"! 



124' J 15'0"T\ 


Figure 3.1.9. Distribution of sampling stations with station numbers for Coos Bay, 
Oregon for the 2002 West Coast Intertidal Assessment. 


21 










> 


Smith River (CA) 


030 


Areata Bay 
Humboldt Bay ^007 
Eel River ooi 022 


013 

i 

023 


e 

£ 

3> 

ZJ 


ZJ 


ZJ 

73 

2 - 


w 




50 


100 


km 







r 



La 

Reckling* 



^■Jl **LT. •, 


iL’V' -*** 2 *? 

h,. 


California 

■ ■ '^/S5"4 





% 

l Ki 


Sc 


gil£$ 


■ 


«gp- 



*<e 


-1- 

124 C 0'0"W 


Bodega Bay 

Tomtits Bay 0( ^ 032 A ^° 4 ^ 4 

n I „ 4 A n?n 620 fe30 626 

Drakes 5^16 003° 2U A ▲ 

_ A 024 A 628 618 


Figure 3.1.10. Distribution of sampling stations with station numbers for the northern 
half of California for the 2002 West Coast Intertidal Assessment. 


22 






632 


A623 


616 


608 

4629 

617 


Elkhont A 014 
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Nevada 


Ar 


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031 

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002 


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cs 




301 343 

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312 


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San Diego 30? 

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317 


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0 25 50 


100 


150 


200 


250 


km 


122°0'0"W 


-1- 

120°0'0"1V 


- 1 - 

118 - 0 ' 0 " IV 


Figure 3.1.11. Distribution of sampling stations with station numbers for the southern 
half of California for the 2002 West Coast Intertidal Assessment. 


23 














124 c 15'0"n 


124°10'0"W 


124~5'0"ir 


Figure 3.1.12. Distribution of sampling stations with station numbers for Areata and 
Humboldt Bays, California for the 2002 West Coast Intertidal Assessment. 


24 










Figure 3.1.13. Distribution of sampling stations with station numbers for San Francisco 
Bay, California for the 2002 West Coast Intertidal Assessment. 


25 








3.2 Sediment Quality 
3.2.1 Sediment Composition 

The sediment grain size distribution can be an important indicator of the benthic 
environment, with the benthic community typically strongly responding to changes in 
grain size composition. Relative accumulation of sediment organic carbon and 
sediment contaminants may be correlated with sediment grain size, with finer grain 
sizes tending to accumulate in lower energy environments. The mean percentage of 
fine particles (silts, clays) in sediments was less than 60% in all five geographic 
categories (Fig. 3.2.1), but was approximately two times greater in samples for 
California and San Francisco Bay than in samples from Oregon and Washington. On 
an areal basis, 28% of western intertidal habitat consisted of sediments with >80% 
fines. Washington (5%) and Oregon (4%) had much lower areas with >80% fines than 
did California (50%) or San Francisco Bay (38%). Appendix Table 3 provides a 
summary of sediment grain size, total organic carbon (TOC), nutrient concentrations 
and contaminant concentrations for all stations. 



Figure 3.2.1. Percent fine sediments for the 2002 West Coast Intertidal Assessment 
(mean ± 1 sd). 


26 
















3.2.2 Sediment Total Organic Carbon 

Another measure of sediment condition is the percent Total Organic Carbon 
(TOC). In the NCCR II report (U.S. EPA 2004), values exceeding 5% TOC were ranked 
poor, values between 2% and 5% were ranked fair, and values less than 2% were 
ranked good. There was a distinct difference in the average value of TOC between 
sites in Washington and Oregon (means <2%) and sites in California, including San 
Francisco Bay (>4%) (Fig. 3.2.2, Appendix Table 3). West wide (excluding high marsh 
in San Francisco Bay), 2.9% of total estuarine intertidal area had values over 5% TOC. 
There was a similar distinction in the amount of intertidal area among states with high 
TOC values, with Washington and Oregon having <2% of area with values over 5% 
TOC, compared with >20% of area for California and San Francisco Bay. 



Figure 3.2.2. Percent sediment total organic carbon (TOC) for the 2002 West Coast 
Intertidal Assessment (mean ± 1 sd). 


27 



















3.2.3 Sediment Nutrients 

Sediments perform the function of removal of nitrogen and phosphorus from the 
water column through the process of sequestration of these nutrients in organic matter 
into the sediments. Nitrogen and phosphorus sequestered in sediments can also be a 
source of dissolved nutrients exported to the water column, where they are essential for 
phytoplankton growth, but in excess may lead to undesirable phytoplankton blooms. 

Average percent sediment concentrations of both total nitrogen and total 
phosphorus were lowest in Washington and highest in California (Figs. 3.2.3, 3.2.4; 
Appendix Table 3). West wide (excluding high marsh in San Francisco Bay), the mean 
value of sediment total nitrogen was less than 0.5 percent in 96% of intertidal area, and 
sediment total phosphorus was less than 0.1 percent in 95% of intertidal area. The 
mean value of sediment total nitrogen was < 0.3 percent in 100% of Washington 
sediments but 0.5 percent or more in 13% of area in Oregon, 18% of San Francisco Bay 
area, and 23% of area in the rest of California. The mean value of sediment total 
phosphorus was 0.1 percent or less in 99% of area in Washington, 98% of area in 
Oregon, 77% of San Francisco Bay area, and 80% of area in the rest of California. The 
five highest values for sediment concentrations of both total nitrogen and total 
phosphorus occurred in sediments from estuary sites within the Southern California 
Bight and from San Francisco Bay (Appendix Table 3). 



Figure 3.2.3. Average percent sediment total nitrogen for intertidal samples obtained in 
2002 for the West Coast region, individual states, and San Francisco Bay (mean 
± 1 sd). 


28 
















0.14 - 


0.12 - 


= 0.10 - 

W 



WEST WA OR CA SF BAY 


Figure 3.2.4. Average percent sediment total phosphorus for intertidal samples 

obtained in 2002 for the West Coast region, individual states, and San Francisco 
Bay (mean ± 1 sd). 


29 
















3.2.4 Sediment Contaminants 

To assess the degree of sediment contamination in West Coast estuaries, the 
sediment concentrations of contaminants were compared with both the ERM and ERL 
guidelines (Long et al., 1995). A total of 28 compounds or groups of compounds were 
included on the list of contaminants used by the NCCR II report (U.S. EPA 2004). The 
analysis of the 2002 intertidal data for West Coast estuaries excluded nickel and two 
PAHs, phenanthrene and dibenzothiophene. Phenanthrene and dibenzothiophene 
were excluded because values were not available from all three states. Nickel was 
excluded because the ERM value has a low reliability for West Coast conditions where 
high natural crustal concentrations of nickel exist (Long et al., 1995; Long et al., 2000; 
Lauenstein et al., 2000). 


Sediment Contaminant Guidelines (Long et al., 1995) 

ERM (Effects Range Median)—Determined for each chemical as the 50th percentile (median) 
in a database of ascending concentrations associated with adverse biological effects. 

ERL (Effects Range Low)—Determined values for each chemical as the 10th percentile in a 
database of ascending concentrations associated with adverse biological effects. 




Sediment concentrations exceeded their respective ERM values at only five 
stations, representing 0.3% of the intertidal estuarine area of the West Coast (Appendix 
Table 3). Four sites were located in Southern California (none in San Francisco Bay), 
one in Oregon, and none in Washington. In all cases, the exceedances of the ERMs 
were due to DDT and/or its congener 4,4’ DDE. Three of the four California sites were 
in Point Mugu Lagoon, and the remaining site was in Newport Harbor. 

Any site that had five or more compounds that exceeded their ERL values was 
classified as having fair condition in the NCCR II report (U.S. EPA 2004). As with the 
ERMs, nickel was excluded from the analysis. To ensure that the analysis was not 
biased by PAHs, only one exceedance was counted if a site exceeded the ERL for 
LMW PAHs, HMW PAHs, or total PAHs. A total of 14 stations had five or more 
pollutants exceeding the ERL value, of which 3 also exceeded one or more ERMs 
(Appendix Table 3). The 14 sites represent only 0.21% of the intertidal area of the West 
Coast estuaries. All of these sites occurred in California, with 5 sites located in either 
high or low marsh within the San Francisco Bay, while the remaining 9 sites were in 
Southern California. Two additional sites, one in California and one in Oregon, had 
sediments pollutants that exceeded one or more ERMs, but had less than five pollutants 
exceeding the ERL (Appendix Table 3). 

Another indicator approach to evaluation of the level of potential problems 
resulting from sediment contamination is the use of the Effects Range Median Quotient 
(ERM-Q, Long and MacDonald, 1998). 


30 



Sediment Effects Range Median Quotient (Long and MacDonald, 1998) 

ERM-Q — The average quotient of the measured concentration of a defined list of 
contaminants divided by their ERM values. 




The ERM-Q index attempts to summarize the overall contaminant exposure 
resulting from a mixture of contaminants by dividing the measured sediment 
concentration of a contaminant by its ERM value, followed by taking an average value 
of these quotients. Average ERM-Q values for samples from California and San 
Francisco Bay were approximately two times higher than those for sites in Washington 
and Oregon (Fig.3.2.5). Thompson and Lowe (2004) have suggested that an average 
ERM-Q of <0.146 was a reasonable guideline for reference condition with regard to 
sediment contamination in the San Francisco Estuary. For a national data set, Long et 
al. (1998) suggested that values <0.1 indicate a low probability (11.6%) of having highly 
toxic sediments. All values of average ERM-Q for the five areas in the present study 
(Fig.3.2.5) are below these guidelines. 


a 


o: 

LU 


0.14 - 

0.12 - 

0.10 - 

0.08 - 

0.06 - 

0.04 - 

0.02 - 

0.00 - 

WEST WA OR CA SF BAY 



Figure 3.2.5. Average Effects Range-Median Quotient (ERM-Q) values for sediment 
contaminant concentrations for intertidal samples obtained in 2002 for the West Coast 
region, individual states, and San Francisco Bay (mean ± 1 sd). 


31 


















3.3 Biological Condition 
3.3.1 Benthic Infauna 

A total of 217 samples were taken in the three states, with 60 samples taken in 
California other than San Francisco Bay, 30 in San Francisco Bay, 66 in Oregon, and 
61 in Washington. Twelve of the 30 San Francisco Bay samples were allocated to the 
“high marsh” frame. The West survey was defined as the 205 samples from the three 
states other than 12 high marsh samples in San Francisco Bay. Although the goal was 
to obtain 0.1 m 2 samples at all these sites, the large volume of detritus retained 
necessitated subsampling 78 (36%) of the benthic samples. Additionally, the actual 
interior area of the post-hole sampler was 0.09 m 2 rather than 0.1 m 2 . These two 
factors resulted in a total of twelve functional sample sizes with sizes ranging from 
0.0028 to 0.1 m 2 . While there was a wide range of sample sizes, the majority of the 
samples (122) were taken with the 0.09 m 2 post-hole digger and 196 of samples fell 
within four sizes (0.0056, 0.0225, 0.09, and 0.1 m 2 ). To account for the differences in 
sample size, all benthic abundances were normalized to 0.09 m 2 . Abundance generally 
increases linearly with area, so this normalization should not introduce much additional 
uncertainty in densities. Flowever, the number of species per sample does not increase 
linearly and accordingly we did analyze absolute species richness or FT on a per sample 
basis. 


The median abundance in the West wide survey was 503 individuals per 0.09 m 2 
(= 5589 m 2 ) with an average density of 1,802 individuals per 0.09 m 2 (=20,022/m 2 ). 

This intertidal density is approximately within the range found in the previous survey of 
primarily subtidal assemblages in the small and moderate sized West Coast estuaries 
(Nelson et al., 2004). Median benthic densities were highest in Oregon at about 1,245 
individuals per 0.09 m 2 (=13,833/m 2 ) and lowest in Washington with 373 individuals per 
0.09 m 2 (=4,144/m 2 ). Average densities showed the same trend, with Oregon having 
the highest average abundance, California and San Francisco having similar 
abundances, and Washington having the lowest average abundance (Figure 3.3.1). 

The lower density in Washington partially reflects the low density in Puget Sound 
(average = 617 individuals per 0.09 m 2 ) compared to the coastal estuaries (average = 
1,256 individuals per 0.09 m 2 ). 

A total of 420 taxa were identified from all 217 samples of which 248 were 
identified to the species level. Presumably the total number of species would have 
been greater if all the samples had been 0.1 m 2 in area and if the “problematic” taxa 
(e.g., oligochaetes, insect larvae) had been identified to species. Taxa were classified 
as native, nonindigenous, cryptogenic, indeterminate taxa, cosmopolitan, or 
unclassified. Cryptogenic species are species of unknown origin (Carlton, 1996) while 
indeterminate taxa are those not identified with sufficient taxonomic resolution to 
classify as native, nonindigenous, or cryptogenic (Lee et al., 2003). Cosmopolitan is 
used primarily for pelagic taxa that are widely dispersed across several oceans, while 
unclassified species are those that have yet to be sufficiently analyzed to render a final 
classification. The classifications used here follow the Pacific Ecosystem Information 
System (PCE/S), a georeferenced database of native and nonindigenous species of the 


32 


Northeast Pacific being developed by the EPA and USGS (Lee and Reusser, 2007). Of 
the 420 taxa, there were 170 native species, 42 nonindigenous species (NIS), 32 
cryptogenic species, 1 cosmopolitan pelagic copepod, 3 unclassified species, and 172 
indeterminate taxa. In terms of relative abundance, polychaetes and oligochaetes were 
the dominant taxa, composing over 40% and 20% of the individuals, respectively 
(Figure 3.3.2). The only other taxa to comprise more than 5% of the individuals were the 
amphipods and bivalves (Table 3.3.1). 

The oligochaetes were not identified to species, but are a reasonably diverse 
taxon with almost 200 species reported from marine, estuarine, and tidal fresh habitats 
in the Northeast Pacific (Lee and Reusser, 2007). Oligochaetes are a numerically 
dominant taxa in a number of Pacific Coast assemblages, including Spartina beds in 
San Francisco (Neira et al., 2005), “fresh-brackish sandy” and “estuarine margin” 
subtidal benthic assemblages in San Francisco Bay (Lee et al., 2003), and Zostera, 
Upogebia, and Spartina habitats in Willapa Bay (Ferraro and Cole, 2007). In the 
present study, oligochaetes were abundant along the entire coast and constituted the 
most abundant or second most abundant taxon in California, San Francisco, Oregon, 
and Washington (Table 3.3.1). The highest oligochaete densities tended to be 
associated with the presence of macroalgae, Zostera marina or Z. japonica beds, or 
marsh habitat including Spartina though moderately high densities also occurred in 
unvegetated flats. Given the number of species on the West Coast, it is likely that 
species composition varied among the habitat types and/or geographically. Because 
certain families of oligochaetes, in particular tubificids, are associated with polluted 
conditions (Engle et al., 1994; Llanso et al., 2002) and because they constitute a major 
proportion of the total individuals in many intertidal assemblages (Figure 3.3.2) we 
recommend that future studies identify oligochaetes at least to the family level. 

The high abundance of polychaetes in these assemblages is fairly typical of other 
soft-bottom assemblages (e.g., Nelson et al., 2004). Less expected was that the single 
most abundant polychaete in the West was the nonindigenous Manayunkia aestuarina , 
a sabellid introduced from the Northeast Atlantic. Manayunkia aestuarina was 
particularly dense in Oregon, much less so in Washington, and not recorded from 
California (Table 3.3.1) though a congener ( Manayunkia speciosa) is abundant in lower 
salinity regions of the San Francisco Bay (Cohen and Carlton, 1995; Lee et al., 2003). 

In Willapa Bay, M. aestuarina has been reported as a numerical dominant primarily 
limited to Spartina alterniflora beds (Ferraro and Cole, 2007). In the present 
probabilistic survey, the greatest abundance of M. aestuarina (148,178/m 2 ) occurred in 
an unvegetated sand flat in Coos Bay, Oregon though high densities were also found in 
Spartina alterniflora in Washington and in Carex lyngbyei , a common shoreline sedge, 
in Oregon. Other abundant polychaetes (average > 20 individuals per 0.09 m 2 sample) 
included two capitellids ( Capitella capitata, Mediomastus califbrniensis), several 
spionids ( Streblospio benedicti, Pygospio elegans, Pseudopolydora paucibranchiata, 
Pseudopolydora kempi, and Polydora cornuta), and a cirratulid (Tharyxparvus). Of 
these, four of the spionids (S. benedicti, P. paucibranchiata, P. kempi, and P. cornuta) 
are nonindigenous and Capitella capitata and Pygospio elegans are cryptogenic. All of 
these species are frequently found in subtidal and intertidal assemblages in the 


33 


Northeast Pacific (e.g., Nelson et al., 2004; Ferraro and Cole, 2007, Lee and Reusser, 
2007). 


The three abundant amphipods (> 20 individuals per 0.09 m 2 sample) were 
Grandidierella japonica, Monocorophium insidiosum, and Americorophium salmonis, the 
first two of which are nonindigenous species. Both nonindigenous amphipods were 
widely distributed, ranging from Southern California up into Puget Sound. In 
comparison, the native A. salmonis was not found in California, though the 1999 EMAP 
survey found it as far south as the San Luis Obispo Bay (Latitude = 35.17) in California. 
The only bivalve with a high average abundance was the nonindigenous Gemma 
gemma, an East Coast species introduced with importation of Atlantic oysters (Cohen 
and Carlton, 1995). Gemma gemma has a limited distribution in the Northeast Pacific 
and has only been reported from nine California estuaries (Lee and Reusser, 2007). 
Gemma gemma was only found in 6% of the samples (Table 3.3.1), and the high 
average West wide abundance reflects its high densities in a few locations in San 
Francisco which reached 141,400/m 2 . 

With non-native species constituting the most abundant polychaete, bivalve, and 
amphipod, an obvious alteration to the intertidal benthic communities on the West Coast 
is the proliferation of nonindigenous species. On a regional scale, one measure of the 
extent of invasion is that 42 nonindigenous species were collected, in addition to 
another 32 cryptogenic, or possible nonindigenous species. Not only was a large 
number of nonindigenous species collected but they were widespread. Eighty-five 
percent of the samples contained at least one nonindigenous species (Figure 3.3.3). 
While nonindigenous species were widespread, the extent of invasion appeared to vary 
among sites. To evaluate patterns in invasion, we propose the following metric for the 
relative species richness of nonindigenous species on a per sample basis: 

%NIS Sp p = NIS S pp/(NIS S pp & Natspp) *100 (Equation 3.3.1) 


where: 

%NISs P p = relative species richness of nonindigenous species per sample 
NISspp = number of nonindigenous species in sample 
Natspp = number of native species in sample 

Only native and nonindigenous species are included so as to limit the analysis to 
species with “known” classifications. Inclusion of the cryptogenic species, unclassified 
species, and indeterminate taxa would increase the level of uncertainty, and make 
interpretation more difficult. By normalizing the number of nonindigenous species to the 
sum of nonindigenous and native species, the index is “well behaved” and scales 
between 0 (no NIS) and 100 (all NIS and no natives), though the metric is undefined if 
there are no nonindigenous or native species. Because the index is based on relative 
species richness rather than absolute numbers of nonindigenous species, the 
differences in sample size will not substantially affect the value of the index assuming 
that the relationship between sample area and number of species collected is similar for 
native and nonindigenous species. Over the small areas of the samples, this 


34 


assumption should generally hold, though the assumption is likely to break down at 
large spatial scales such as comparing point samples to total assemblages (Lee et al., 
2003). 


The distribution of the extent of invasion based on the relative species richness 
of nonindigenous species for all 217 benthic samples is shown in Figure 3.3.3. Two 
thresholds seem intuitive in interpreting this metric. The first is simply that the site is 
“uninvaded” if there are no nonindigenous species. Across the West, nonindigenous 
species are absent in 15% of the samples. The second proposed threshold is samples 
in which nonindigenous species constitute >50% of the combined native and 
nonindigenous species. Since nonindigenous species constitute at least half of the 
classified taxa, these sites can be considered to constitute a non-native assemblage 
and are classified as “highly invaded”. Approximately 42% of the samples are classified 
as highly invaded based on this threshold. 

There appear to be substantial differences in the extent of invasion both 
geographically and by habitat type (Figure 3.3.4). To better highlight these differences, 
this analysis separates the San Francisco high marsh samples from the rest of the San 
Francisco habitats and Puget Sound from the rest of the Washington samples even 
though they were not originally identified as separate reporting units. To test for 
significance among locations, a Kruskal-Wallis one-way Analysis of Variance on ranks 
was performed on the values of %NIS Spp from California without San Francisco, San 
Francisco without high marsh, San Francisco high marsh, Oregon, coastal Washington, 
and Puget Sound. Based on this nonparametric test, there is a significant difference in 
the median values of %NIS Spp among these six geographical areas or habitat types (p < 
0.05). San Francisco habitats other than the high marsh were the most invaded with an 
average of almost 50% of the classified species per sample consisting of nonindigenous 
species. The high marsh in San Francisco was less invaded, but this pattern may at 
least partially reflect that these sites had relatively high proportions of oligochaetes and 
insects that were not identified to species. The other apparent pattern is that the 
intertidal benthos in Puget Sound is less invaded. On average, Puget Sound samples 
contained about 26% nonindigenous species compared to 40% to 44% for coastal 
Oregon and Washington. 

The extent of invasion can also be measured by the relative abundance of 
nonindigenous species. Using the same approach as with non-native species richness, 
the relative abundance of nonindigenous species is calculated as a percentage of the 
combined abundance of natives and nonindigenous species as: 

%NIS A bun = NIS A bun/(NIS A bun & Nat Abun ) *100 (Equation 3.3.2) 


where: 

%NIS Ab un = relative abundance of nonindigenous species per sample 
NIS A bun = abundance of nonindigenous species in sample normalized to 0.09 m 2 
Nat A bun = abundance of native species in sample normalized to 0.09 m 2 


35 


As with the metric based on relative species richness on nonindigenous species, 
15% of the samples contained no nonindigenous species (Figure 3.3.5). Another 46% 
of the sites were “highly invaded” as defined by nonindigenous species constituting 
>50% of the individuals. The pattern of the relative abundance of non-native species 
(Figure 3.3.5) differs from that based on the relative species richness of invaders 
(Figure 3.3.3) by having peaks at both “low to moderate” levels of invasion (>0 and 
<25%) and another at “very high” levels of invasion (>75%). This bimodal pattern 
reflects, at least in part, apparent geographical and habitat differences in the extent of 
invasion (Figure 3.3.6). The significance of these geographical/habitat differences was 
tested using a Kruskal-Wallis one-way Analysis of Variance on ranks, which found a 
highly significant difference (p < 0.01) in the median values of %NIS A bun among the six 
geographical areas or habitat types. The benthic assemblages in San Francisco 
exclusive of the high marsh were the most invaded, with an average of 61% of the 
individuals per sample consisting of nonindigenous species. The coastal estuaries of 
Oregon and Washington were also highly invaded with about 50% of the individuals per 
sample consisting of nonindigenous species. In comparison, nonindigenous species 
constituted less than 25% of the individuals in samples from Puget Sound, and less 
than 40% in samples from California other than San Francisco and in the San Francisco 
high marsh. Again the lower extent of invasion in the San Francisco high marsh may 
partially reflect that the oligochaetes and insects were not identified to species. 

Based both on relative species richness and relative abundance, it is apparent 
that the community composition and structure of the intertidal assemblages of 
California, Oregon, and Washington have been substantially altered by the invasion of 
nonindigenous species. These alterations are likely to continue as existing 
nonindigenous species increase their range and/or abundance. For example, the 
nonindigenous amphipod Grandidierella japonica has expanded its range from its first 
sighting in San Francisco in 1966 (Chapman and Dorman, 1975) to 46 Northeast Pacific 
estuaries ranging from Tijuana Estuary to Puget Sound by 2002 (Lee and Reusser, 
2007). After a major flood event in 1996, G. japonica became one of the numerically 
dominant amphipods in the Yaquina Estuary, Oregon (Lee et al., submitted) and it has 
become the most abundant intertidal amphipod on the West Coast (Table 3.3.1). 
Intertidal assemblages will also continue to change in response to new invasions. As 
recently as July, 2007, a “major new snail invasion” (“ Assiminea " sp) was reported for 
Coos Bay, Oregon (J. Carlton, August 31,2007 email). The present probabilistic survey 
provides a baseline of the structure of benthic assemblages as of 2002, and it will be 
important to conduct similar regional surveys in the future to assess the extent and 
nature of changes due to invasion as well as other regional drivers such as climate 
change, habitat alteration, and increased nutrient loading. 


36 


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I s *- 

CO 

o 

LO 

CO 

M" 

o 

M" 

r-- 

CNJ 

o 

CO 

CNJ 

CO 

co 

CNJ 

h- 

00 

co 

00 

CM 

CM 

o 

m 

CM 

M" 

o 

West 

Average 

N = 205 

343.3 

235.9 

112.4 

89.7 

89.0 

74.2 

71.8 

70.4 

49.7 

46.2 

32.0 

25.9 

24.5 

22.1 

21.8 

21.7 

19.8 

Classifi¬ 

cation 

Indeter 

SIN 

SIN 

SIN 

Crypto 

SIN 

Native 

Crypto 

Crypto 

Native 

SIN 

SIN 

SIN 

Native 

Native 

SIN 

SIN 

Taxa 

Code 

O 

Q_ 

CD 

AM 

CL 

0. 

CL 

VI 

CL 

AM 

AM 

CL 

0l 

CL 

OQ 

CL 

Q_ 

Species/Taxon 

Oligochaeta 

Manayunkia 

aestuarina 

Gemma gemma 

Grandidierella japonica 

Capitella capitata 

Streblospio benedicti 

Mediomastus 

californiensis 

Leptochelia dubia 

Pygospio elegans 

Americorophium 

salmonis 

Monocorophium 

insidiosum 

Pseudopolydora 

paucibranchiata 

Pseudopolydora kern pi 

Tharyx parvus 

Macoma balthica 

Polydora cornuta 

Hobsonia florida 


r- 

co 






























0.0 

0.8 

CD 

14.2 

0.0 

o 

o 

2.6 

5.8 

0.8 

21.5 

9.5 

0.0 

CM 

5.5 

28.3 

2.9 

q 

d 

6.5 

o 

o 

1.2 

0.1 

23.4 

o 

o 

0.3 

4.4 

o 

o 

2.6 

00 

o 

d 

51.7 

25.9 

33.3 

0.0 

o 

o 

35.9 

31.5 

2.8 

13.8 

21.1 

0.0 

r- 

00 

19.7 

1.1 

4.5 

O' 

d 

CM 

18.9 

0.0 

4.7 

o 

o 

0.0 

20.1 

00 

13.9 

17.6 

14.4 

o 

o 

00 

00 

00 

o 

d 

10.1 

00 

0.8 

o 

d 

0.2 

2.8 

o 

d 

63.5 

0.3 

0.1 

0.0 

0.0 

o 

d 

0.0 

10.8 

o 

d 

o 

d 

0.0 

o 

d 

0.0 

0.0 

0.0 

0.3 

26.4 

61.1 

0.0 

23.5 

0.0 

44.3 

in 

d 

0.4 

o 

d 

35.1 

0.2 

0.4 

0.1 

00 

o 

CO 

0.0 

22.1 

0.3 

0.1 

20.9 

18.4 

24.1 

o 

d 

00 

19.8 

CM 

d 

00 

SO 

6.5 

2496 

1758 

1304 

396 

1168 

2780 

1344 

LLV 

^r 

CD 

00 

516 

619 

1127 

174 

CO 

CO 

O’ 

364 

281 

1744 

318 

o- 

in 

in 

364 

596 

00 

CM 

O’ 

965 

1058 

192 

CD 

D 

335 

672 

in 

00 


22 


- 

CM 

24 

- 

CM 

- 

CM 

34 

46 

"O' 

20 

- 

23 

CO 

CO 

in 

- 

CD 

o- 

30 

in 

20 

CO 

17.9 

16.9 

CD 

CD 

15.0 

14.4 

13.6 

12.6 

11.9 

11.5 

CO 

9.7 

9.3 

9.2 

8.9 

8.8 

00 

00 

8.6 

8.0 

LL 

7.3 

T — 

r^’ 

oz 

6.5 

5.9 

5.8 

5.7 

CD 

in 

5.3 

Indeter 

Indeter 

SIN 

SIN 

Native 

Native 

SIN 

Indeter 

Crypto 

SIN 

Native 

SIN 

SIN 

Crypto 

Indeter 

Indeter 

Native 

Native 

Native 

Native 

o 

Q. 

o 

Crypto 

Indeter 

Native 

Native 

Native 

SIN 

SIN 

AM 

AN 

VI 

Q_ 

O 

AM 

CU 

0. 

O 

o 

Q_ 

AM 

AM 

CD 

CO 

0. 

AM 

z 

Q_ 

CD 

CL 

AM 

Q_ 

CL 

z 

ISO 

CD 

AM 

AM 

O 

Paracorophium sp. 

Halcampidae 

Sinelobus stanfordi 

Heteromastus filiformis 

Assiminea californica 

Americorophium 

stimpsoni 

Nippoleucon 

hinumensis 

Harpacticoida 

Exogone lourei 

Monocorophium 

acherusicum 

Americorophium 

spinicorne 

Potamocorbula 

amurensis 

Mya arenaria 

Eteone californica 

Ampithoe spp. 

Chironomidae 

Novafabricia brunnea 

Cryptomya californica 

Heteromastus 

filobranchus 

Allorchestes angusta 

Dipolydora socialis 

Chone duneri 

Ceratopogonidae 

Gnorimosphaeroma 

oregonense 

Macoma nasuta 

Eobrolgus chumashi 

Ampithoe valida 

Myosotella myosotis 










































00 

1.4 

eo 

9.2 

0 0 

o 

CD 

14.1 

15.2 

3.8 

00 

90 

CO 

T — 

o 

o 

2.5 

0 0 

CO 

o 

so 

00 

2.0 

I s - 

CD 

570 

C\l 

CO 

548 

5 

577 

CD 

CM 

CM 

xr 

43 

- 

5.3 

LO 

5.0 

4.9 

4.9 

Indeter 

Indeter 

Native 

Native 

Indeter 

SO 

AM 

ISO 

CL 

NE 

Podocopida 

Corophiidae 

Gnorimosphaeroma 

insulare 

Glycinde polyqnatha 

Nemertea 
















10000 


8000 - 

a 

o 

c 

re 

T3 

C 

5 6000 - 

< 

re 

c 

3 

— 4000 - 

o 



Figure 3.3.1. Average total benthic abundance for intertidal samples obtained in 2002 
for the West Coast region, individual states, and San Francisco Bay (mean ± 1 
sd). 



Figure 3.3.2. Relative abundance of the major taxa for intertidal samples obtained in 
2002 for the West Coast region. 


40 






















%NIS by Species 


Figure 3.3.3. Percent of nonindigenous species relative to the number of 

nonindigenous and native species per sample (%NISs PP ). Analysis based on all 
sites including the high marsh in San Francisco with the exception of three 
samples with no nonindigenous or native species (N = 214). 


100 


80 - 



Figure 3.3.4. Average percent of nonindigenous species relative to the number of 

nonindigenous and native species per sample (%NIS Spp ) by location for intertidal 
samples obtained in 2002. 


41 
























%NIS by Abundance 


Figure 3.3.5. Relative abundance of nonindigenous species relative to the abundance 
of nonindigenous and native species per sample (%NIS AbU n). Analysis based on 
all sites including the high marsh in San Francisco with the exception of three 
samples with no nonindigenous or native species (N = 214). 

120 i- 


100 - 



Figure 3.3.6. Average percent of nonindigenous species relative to the abundance of 

nonindigenous and native species per sample (%NIS A bun) by location for intertidal 
samples obtained in 2002. 


42 
























3.3.2 Plant Community 

Vegetation data were collected from both a quadrat and along a transect at each 
site, and data from these two approaches are presented separately. Vegetation percent 
cover, maximum plant height (emergent macrophyte) or leaf length (seagrass), and 
biomass of each taxon were recorded from each vegetation quadrat. Only vegetation 
percent cover was estimated along each transect. 

Quadrat Species Assemblages and Percent Cover 

Vegetation was present in the quadrats at 150 of the 217 sites sampled. The 
types of vegetation recorded within the quadrats included 28 emergent macrophytes, 2 
seagrasses, and macroalgal taxa (Appendix Table 4). Three emergent macrophytes, 
Cotula coronopifolia, Lepidium latifolium, and Spartina alterniflora, are nonindigenous 
species. Two species of seagrass, Zostera marina and Z. japonica (nonindigenous) 
were recorded. These seagrass species were found at 21 and 24 sites, respectively. 
Three groups of macroalgae, green algae, brown algae and red algae, were identified in 
the quadrats. Green algae (e.g., Ulva, Cladophora, Enteromorpha) occurred at 84 sites. 
Red algae were observed at one site and brown algae at six sites. As macroalgae were 
only identified to major taxonomic group, it could not be determined if any 
nonindigenous algal species were present. 

Throughout the West, the vegetation quadrats were dominated by bare area 
(Figure 3.3.7). Relative cover by bare area ranged between 2 and 100% throughout the 
West (Appendix Table 5). Mean relative cover of emergent macrophytes (26%) was 
higher than that of seagrass (9%) or algae (16%) throughout the West (Figure 3.3.7). 
The relative cover of emergent macrophytes ranged between 1 and 100% in the West 
(including all San Francisco sites) (Appendix Table 5). Most emergent macrophyte taxa 
occurred at only a few sites (Appendix Table 4). Eighty-two percent of taxa occurred at 
three or fewer sites. The most frequently occurring emergent macrophyte taxa were 
Jaumea carnosa and Salicornia virginica. The paucity of emergent vegetation at most 
sites may be attributed to the fact that most of the sites in the sample frame were 
classified as unvegetated tide flats (Figure 3.1.2). 

The relative cover by major plant groups (emergent macrophytes, seagrass, 
macroalgae) and bare area displayed geographic patterns (Figure 3.3.7). Bare area 
was highest for sites in Oregon and Washington, while cover by emergent macrophytes 
was highest in California and San Francisco Bay. Mean bare area was 62% in Oregon 
and 63% in Washington. Mean bare area was 42% in California and 42% for sites in 
San Francisco Bay. Mean relative cover of emergent macrophytes was 3% in 
Washington and 7% in Oregon and 38% in California and 62% in San Francisco Bay. 
Cover of emergent macrophytes was higher than that of algae or seagrass in California 
and San Francisco Bay sites. Relative cover of seagrass was higher than that of 
emergent macrophytes in Oregon and Washington sites. Mean relative cover of 
seagrass was less than that of emergent macrophytes or algae in California sites. 

Mean relative cover of algae (all types) was highest for Oregon sites (Figure 3.3.7). 


43 


Geographic patterns in cover of major plant groups may be attributed to differences in 
habitat types among states. Over 80% of Washington sites were classified as tidal flat 
and no sites were classified as marsh (Figure 3.1.2). In contrast, approximately 40% of 
sites in California and San Francisco Bay were classified as marsh. Oregon sites were 
a mixture of habitat sites, with more sites in the submerged aquatic vegetation (SAV) 
habitat class than other states. 

Taxa occurrence and mean relative cover of common emergent taxa also 
displayed geographic patterns (Appendix Table 5). The greatest number of emergent 
macrophyte species were observed in California (n = 11) and San Francisco Bay (n = 
17). Six emergent macrophyte species were observed in Oregon. The quadrats of only 
three sites in Washington had emergent macrophyte cover and only one species, S. 
alterniflora, was present in these quadrats. Because most taxa only occurred at a few 
sites, average percent cover of taxa was calculated as the average cover at sites where 
the taxa occurred and not across all sites. Mean cover of S. virginica was 39% in 
California sites and 70% in San Francisco Bay sites (Figure 3.3.8). This species 
occurred at one site in Oregon and was not present in Washington. Mean cover of J. 
carnosa was 43% in California sites and 30% in San Francisco Bay. This species was 
not present in Oregon or Washington sites. The three remaining species occurring at 
more than five sites, Batis maritima, Distichlis spicata, and Spartina foliosa, were only 
encountered in California and San Francisco Bay sites. Geographic patterns in 
occurrence and cover of common emergent macrophyte species may again be 
attributed to differences in habitat types among states. While tidal marsh macrophytes 
can tolerate inundation, these species can not tolerate the prolonged periods of 
inundation experienced on tidal flats and therefore are restricted to habitats receiving 
less inundation. 

Seagrass species were observed in the quadrats of California, Oregon and 
Washington sites. Zostera marina was present in the vegetation quadrats of all three 
states (Appendix Table 5). Mean relative cover of Z. marina was highest for 
Washington sites (Figure 3.3.9). For Washington sites, mean relative cover of the 
invasive seagrass, Z. japonica, was higher than that of Z. marina, 44% and 27%, 
respectively. Zostera japonica did not occur in California or San Francisco Bay (Figure 
3.3.10). Mean relative cover of green algae was highest in California (70%). Green 
algae did not occur in San Francisco Bay sites (Figure 3.3.11). 

Nonindigenous species (emergent macrophytes and seagrass) were 
encountered in the quadrats at 29 sites throughout the study area. Spartina alterniflora 
was observed at three sites in Washington and Z. japonica was observed at sites in 
both Oregon and Washington. Lepidium latifolium was found at one site in San 
Francisco Bay. Mean relative cover of nonindigenous species was low (8%) throughout 
the West (Figure 3.3.12). Mean cover by nonindigenous species was highest in 
Washington (21%), with nonindigenous species being found at 20 sites. Sites in 


44 


Washington had both S. alterniflora and Z. japonica. No nonindigenous species were 
observed at California sites. 

Quadrat Emergent Macrophyte Height and Seagrass Maximum Length 

For most emergent species, maximum plant height/length were recorded at fewer 
than 5 sites throughout the study area, making this a problematic variable to evaluate as 
a potential indicator (Appendix Table 6). Maximum height of S. virginica was recorded 
at 29 sites throughout the West (not including San Francisco Bay), ranging between 6 
and 76 cm. Maximum length of this species was recorded at 15 sites in San Francisco 
Bay. The mean value at these sites was 49 cm. Maximum blade length of seagrass 
was recorded at most sites when present. For the West overall, blade lengths of Z. 
marina (range 14-122 cm) were longer than those of Z. japonica (range 7-38 cm). 

Quadrat Biomass 

Total biomass in the vegetation quadrat throughout the study ranged between 0 
and 800 g/m 2 dry weight. Total biomass was greatest for sites in San Francisco Bay 
(mean = 350 g/m 2 ) and California (mean = 193 g/m 2 ; Figure 3.3.14). This can be 
attributed to the fact that these sites had greater cover by vegetation of all types while 
Oregon and Washington sites had more bare cover (Figure 3.3.7). For the West overall 
(not including San Francisco Bay), algae contributed the most to quadrat biomass 
(mean = 44%; Figure 3.3.14), followed by emergent macrophytes (mean = 38%) and 
seagrass (18%). This finding can be attributed to the fact that for many sites in Oregon 
and Washington, only macroalgae were present in the vegetation quadrats. In contrast, 
emergent macrophytes were the major contributor to quadrat biomass in San Francisco 
Bay and California sites. Emergent macrophytes contributed 99% on average to 
quadrat biomass in San Francisco Bay sites and 67% to quadrat biomass in California 
sites. The geographic patterns in relative contribution of different plant types to total 
quadrat biomass may again be attributed to differences in habitat types, and 
subsequently vegetation groups, among states. Tidal wetland habitat in California and 
San Francisco Bay is dominated by marsh habitat and emergent macrophyte 
vegetation. Oregon sites were a mixture of habitat types and thus different vegetation 
types contributed to quadrat biomass at different sites. Washington sites are classified 
primarily as tidal flat. Subsequently, seagrass and macroalgae are the major 
contributors to quadrat biomass. 

Mean biomass of emergent macrophytes varied among the states, attributable to 
geographic differences in macrophyte taxa encountered. For example, the only 
emergent macrophyte observed in the quadrats of Washington sites was S. alterniflora, 
a relatively large, perennial grass. In contrast, sites in California, San Francisco Bay 
and Oregon had a mix of macrophyte taxa of different growth forms. Most emergent 
macrophyte taxa were only found at a few sites (and weights recorded at even fewer), 
making it difficult to evaluate geographic trends in biomass. Biomass of most emergent 
macrophyte taxa was greater than that of seagrass species or macroalgal taxa 
(Appendix Table 7). Mean biomass of Z. marina and Z. japonica in the West were 


45 


similar, 14 and 13 g/m 2 , respectively. Biomass of these species was similar in Oregon 
and Washington. Mean biomass of green algae was similar in California (mean = 26 
g/m 2 ) and Oregon (mean = 30 g/m 2 ) and somewhat lower in Washington (mean = 9 
g/m 2 ). As algae were only classified into large taxonomic groups, it is difficult to explain 
geographic differences in biomass. 

Transect Species Assemblages and Percent Cover 

Vegetation was present along the transects at 171 sites of the 217 sites sampled. 
Vegetation recorded on transects included 31 emergent macrophytes, including three 
nonindigenous species (C. coronopifolia, L. latifolium, and S. alterniflora), two 
seagrasses (Z. marina and Z. japonica), and algal taxa (Appendix Table 4). 

Seagrasses were found at 25 and 28 sites, respectively. Three groups of macroalgae, 
green algae, brown algae and red algae, were identified in the transects. Green algae 
(e.g., Ulva, Cladophora, Enteromorpha) were observed at 84 sites. Red algae were 
observed in one transect and brown algae in four transects. 

Throughout the West, the vegetation quadrats were dominated by bare area 
(Figure 3.3.15). Relative bare area ranged between 4 and 100% throughout the West 
(Figure 3.3.15). Mean relative cover of emergent macrophytes (21%) and macroalgae 
(20%) were similar and higher than that of seagrass (9%) throughout the West (Figure 
3.3.15). The relative cover of emergent macrophytes ranged between 1 and 100% in 
the West (including all San Francisco Bay sites) (Appendix Table 8). Most emergent 
macrophyte taxa occurred in the transects of only a few sites (Appendix Table 4), with 
84% of taxa occurring at three or fewer sites. The most frequently occurring emergent 
macrophyte taxa were S. virginica, J. carnosa, D. spicata and Spartina foliosa. Similar 
to the vegetation quadrats, the low emergent vegetation cover at most sites may be 
attributed to the fact that most of the sites in the sample frame were classified as 
unvegetated tide flats (Figure 3.1.2). 

Percentage of bare area in the transects was higher for sites in Oregon and 
Washington than those in California (Figure 3.3.15). Mean percentage of bare area was 
59% in Oregon and 60% in Washington. Mean bare area was 38% in California and 
36% for sites in San Francisco Bay. The relative cover by major plant groups 
(emergent macrophytes, seagrass, algae) displayed geographic patterns. Relative 
abundance of emergent macrophytes was lower in Washington (mean = 3%) and 
Oregon (mean = 9%) than for sites in California (mean = 43%) and San Francisco Bay 
(mean = 78%). Relative cover of seagrass was higher than that of emergent 
macrophytes at Washington sites (Figure 3.3.15). Cover of emergent macrophytes was 
higher than that of algae or seagrass in California and San Francisco Bay sites. Mean 
relative cover of seagrass was 0% in California and San Francisco Bay sites. Mean 
relative cover of algae (all types) was higher than that of emergent macrophytes and 
seagrass in Oregon sites (Figure 3.3.15). Mean relative cover of algae (all types) was 
highest for Oregon sites. Cover of emergent macrophytes was higher than that of algae 
or seagrass in California and San Francisco Bay sites. Similar to vegetation quadrats, 


46 


geographic patterns in transect vegetation cover of major plant groups can be attributed 
to differences in habitat types among states. Marsh habitat was more common in 
California and San Francisco Bay, while tidal flat habitat was more abundant in 
Washington and Oregon. 

Taxa occurrence and mean relative cover of common vegetation taxa in the 
transects also displayed geographic patterns. The largest numbers of emergent 
macrophyte species were observed in the transects of sites in California (n = 11) and 
San Francisco Bay (n = 18), although most of these species occurred at fewer than 3 
sites. Nine emergent macrophyte species were observed in the transects of Oregon 
sites. The transects of only four sites in Washington had emergent macrophyte cover 
and only two species, Juncus gerardii and S. alterniflora, were present in Washington. 
Because most taxa only occurred at a few sites, average percent cover of taxa was 
calculated as the average cover at sites where the taxa occurred and not across all 
sites. Mean cover of S. virginica was 48% in California sites and 76% in San Francisco 
Bay sites (Figure 3.3.16). This species occurred at one site in Oregon and was not 
found in Washington. Mean cover of J. carnosa was 39% in California sites. This 
species was present at one site in San Francisco Bay and was present in neither 
Oregon nor Washington sites. Of the three remaining species occurring at more than 
five sites, B. maritima and S. foliosa were only encountered in California and San 
Francisco Bay sites. Distichlis spicata was not observed in Washington. Again similar 
to vegetation quadrats, geographic patterns in occurrence of common emergent 
macrophyte taxa may be attributed to differences in habitat types among states 

Seagrass species were observed in the quadrats of California, Oregon and 
Washington sites. Zostera marina was present in the vegetation transects of all three 
states. Mean relative cover of Z. marina was similar for Washington and Oregon sites 
(Figure 3.3.17). For Washington sites, mean relative cover of the invasive seagrass, Z. 
japonica, was higher than that of Z. marina, 52% and 28%, respectively. Zostera 
japonica did not occur in California or San Francisco Bay (Figure 3.3.18). Mean relative 
cover of green macroalgae was highest at California sites (63%; Figure 3.3.19). Green 
macroalgae did not occur in San Francisco Bay. 

Nonindigenous emergent macrophytes and seagrass were encountered in the 
transects at 33 sites throughout the study area. Spartina alterniflora was observed at 
three sites in Washington and Z. japonica was observed at sites in both Oregon and 
Washington. Lepidium latifolium was found at one site in San Francisco Bay. Mean 
relative cover of nonindigenous species was low (14%) throughout the West (Figure 
3.3.20). Mean cover by nonindigenous species was highest in Washington (37%), with 
nonindigenous species being found at 21 sites. Sites in Washington had both S. 
alterniflora and Z. japonica. No nonindigenous species were observed at California 
sites. 


47 


Summary of Vegetation Results 

Overall, cover by vegetation in tidal wetlands in the West was low, with bare area 
dominating both the quadrats and transects at many sites. The small number of 
vegetation species observed at each site makes it difficult to evaluate community 
patterns and the low frequency of occurrence of most species makes it difficult to 
evaluate patterns of individual species across the study area. Observed geographic 
patterns in major plant groups may be attributed to differences in habitat type among 
the three states. The higher abundance of emergent macrophytes in California and San 
Francisco Bay sites may be attributed to the predominance of marsh habitat in these 
areas. The higher abundance of seagrass and macroalgae in Washington may be 
attributed to the predominance of tidal flat habitat and lack of marsh habitat in this state. 
Oregon tidal wetlands were a mixture of habitat types and subsequently, these sites 
contained a mixture of vegetation groups. 

Plant cover data generated from vegetation quadrats and vegetation transects 
were very similar throughout the study area. Geographic trends in major plant groups 
and common individual species were similar for quadrat and transect data. Species 
richness throughout the study area was slightly higher and relative cover of bare area 
was slightly lower for transect data than quadrat data. These findings may be attributed 
to the fact that sampling area was larger for transects (5-m length) than quadrats (0.25 
m 2 ). Vegetation sampling in tidal wetlands often employs much longer transects (for 
example 30-m; Bertness and Ellison 1987) running perpendicular to the shoreline to 
capture heterogeneity in tidal wetland vegetation in response to gradients in inundation 
and salinity. As transects in this study were short and were established parallel to the 
shoreline, they would not be expected to capture this variation in vegetation, potentially 
resulting in the low number of species encountered at most sites. 


48 


100 - 


03 

> 

o 

O 

c 

03 

QJ 


TO 

■D 

03 

o 


80 - 


60 - 


40 - 


20 - 



WEST 


WA 


OR 


I 

CA 


I I Bare 

l l Emergent 

I I Seagrass 

■■ Algae 
I I Other 


SF BAY 


Figure 3.3.7. Mean relative abundance of vegetation groups and bare area in 
vegetation quadrats. 

120 n- 


03 

o 



Figure 3.3.8. Relative percent cover of Salicornia virginica in the vegetation quadrats at 
sites where present (mean ± 1 sd). 


49 














































Figure 3.3.9. Relative percent cover of Zostera marina in the vegetation quadrats at 
sites where present (mean ± 1 sd). 


<0 

o 

c 

o 

a 

<0 


2 


0) 

</) 

o 


N 


<D 

> 

O 

o 


re 

*o 

re 

3 


O 


100 


80 - 


60 - 



WEST WA OR 


CA 


I 

SF BAY 


Figure 3.3.10. Relative percent cover of Zostera japonica in the vegetation quadrats at 
sites where present (mean ± 1 sd). 


50 
























120 



Figure 3.3.11. Relative percent cover of green algae in the vegetation quadrats at sites 
where present (mean ± 1 sd). 



Figure 3.3.12. Relative percent cover of nonindigenous species in the vegetation 
quadrats at sites where plants are present (mean ± 1 sd). 


51 


























Mean Proportion of Quadrat Biomass (%) 


600 


cti - '' 500 - 

E 

3 

$ 400 - 


E 

o 



WEST WA OR CA SF BAY 


Figure 3.3.13. Total vegetation (emergent macrophytes, seagrass, algae) biomass in 
the vegetation quadrats (mean ± 1 sd). 



Figure 3.3.14. Mean proportion of quadrat biomass for each vegetation group. 


52 










































Bare 


□ Emergent 

□ Seagrass 
■ Algae 

H Other 


Figure 3.3.15. Mean relative abundance of vegetation groups and bare area in 
vegetation transects. 



Figure 3.3.16. Relative percent cover of Salicornia virginica in the vegetation transects 
at sites where present (mean ± 1 sd). 


53 












































100 - 


co 



WEST WA OR CA SF BAY 

Figure 3.3.17. Relative percent cover of Zostera marina in the vegetation transects at 
sites where present (mean ± 1 sd). 


(0 ioo - 
,o 

c 

o 

a 


0 ) 

</> 

o 

N 60 - 



WEST WA OR CA SF BAY 

Figure 3.3.18. Relative percent cover of Zostera japonica in the vegetation transects at 
sites where present (mean ± 1 sd). 


54 























100 - 


<D 

03 

U) 



WEST WA OR CA SF BAY 


Figure 3.3.19. Relative percent cover of green algae in the vegetation transects at sites 
where present (mean ± 1 sd). 

(0 100 1 - 

0) 

o 

(D 

Q. 

</) 

(/) 80 - 

o 

c 

0) 

o> 

1 60 - 

l 

c 

O -T- 


40 - 



WEST WA OR CA SF BAY 

Figure 3.3.20. Relative percent cover of nonindigenous species in the vegetation 
transects at sites where plants are present (mean ± 1 sd). 


55 


























3.4 Shoreline Land Use 

West wide, approximately an estimated 55% of estuarine area had shoreline 
immediately adjacent that was classified by field crews as undeveloped. In Washington 
and Oregon, much of the undeveloped land was in silviculture. Somewhat surprisingly, 
across the three states, the percentage of area with adjacent shoreline classified as 
residential was very similar, on the order of 20%. California and San Francisco Bay had 
much higher area with urban shoreline adjacent to the intertidal sampling points than did 
Washington and Oregon. 


120 







ZX2 



Agriculture 

Undeveloped 

Residential 

Recreational 

Oyster Aquaculture 

Armored 

Industrial 

Highways 

Other 

Urban 


Figure 3.4.1. Percentage areas within assessment regions with shoreline adjacent to 
sample locations in different land use categories. 


3.5 Lessons Learned 

Tidal wetlands constitute critical habitats in West Coast estuaries, although their 
nature varies geographically. In the Pacific Northwest, tidal wetlands predominantly 
consist of unvegetated sand and mud flats, with marshes limited to a relatively narrow 
band along the upper edge of the bathymetric gradient. In comparison, vegetated 
wetlands constitute a much greater proportion of the total estuarine area in San 
Francisco Bay and in estuaries in Southern California. The results presented here 
represent the first regional scale survey of the condition of these habitat types on the 
West Coast and, to the best of our knowledge, anywhere. As such, these results 
constitute a critical baseline by which to evaluate changes in response to continued or 


56 









































increasing anthropogenic stress from excessive nutrient loading, urbanization, shoreline 
modification, invasion of nonindigenous species, and the host of potential alterations 
resulting from global climate change. 

Sampling the range of vegetated and unvegetated tidal wetlands was not a 
simple endeavor but the approaches used in this survey, from use of hovercraft to 
quantifying burrowing shrimp, generally proved feasible for regional scale surveys of 
wetland condition. A slightly modified version of these approaches has since been used 
in another tidal wetland survey (Lee et al., 2006). This is not to say that improvements 
could not be made. 

In the sample design, with the exception of San Francisco Bay, sample sites 
were selected at random, with no attempt to require that sample sites fell within marsh 
habitats within a given multidensity category. The sample distribution by habitat type 
thus reflects the relative distribution of habitat types in the estuarine intertidal of the 
West Coast, but does mean that marsh type habitats had relatively few samples from 
some states. In hind sight, the habitat maps available appear to have been sufficiently 
accurate to have allowed partitioning of sample effort by habitat type. 

The use of the shoreline development indicator proved to be somewhat variable 
among field crews, suggesting a need for more careful a priori definition of shoreline 
development categories, and development of a photographic guide to assist field crews 
in providing a consistent classification. 

A difficult issue that arose was the need to subsample benthic samples due to 
the extreme processing time for some samples, especially those collected in vegetated 
wetlands. The consequence of this practice, which was carried out with differing 
subsample sizes by different state laboratories and contractors, was the generation of 
biological samples based on effectively different surface areas. We recommend that if 
at all possible, sufficient dollar and time resources be allocated to fully process the 0.1 
m 2 benthic samples regardless of the volume of residue. If that is not practical, then one 
possibility is to subsample all 0.1 m 2 benthic samples with a smaller core and process 
these independently. This approach would allow the comparison among all sites within 
a study using the smaller, standardized sample size, while maintaining the ability to 
compare the sites sampled with the 0.1 m 2 area with previous EMAP efforts. Another 
issue is the high abundance of oligochaetes and, to a lesser extent, insects in several 
tidal wetland habitats. Both of these are difficult taxa to identify, but to the extent 
practical they should be identified to species or at least to family. 

The other major ecological endpoints used in this survey were tidal wetland plant 
composition, cover, and biomass. One goal of the plant survey was to evaluate the 
potential for development of wetland indicators. However, one of the lessons learned is 
that the number of plant species in the 0.25 m 2 quadrat or 5-m transect is too low for 
use in most of the standard benthic indicators based on species richness. Another 


57 


lesson was that most plant species only occurred in a limited number of sites, making it 
difficult to develop generally applicable metrics based on indicator species. While the 
present effort was not sufficient to develop wetland indicators by itself, it did feed into 
the development of the California Rapid Assessment Method (CRAM; 
http://www.cramwetlands.org/ ) and to similar rapid assessment surveys being 
conducted by U.S. EPA in Oregon. 

3.6 Summary 

Condition of the soft sediment habitat within the intertidal zone of the states of 
Washington, Oregon and California, with the exception of the estuarine portion of the 
Columbia River, was successfully assessed at 217 sites during the summer of 2002. 

The dominant types of estuarine intertidal habitat varied among the three states, 
although unvegetated sand or mud flats were the dominant habitat types for all three 
states. Shellfish beds (oysters), gravel bottom, and intertidal seagrasses were recorded 
only in Washington and Oregon. San Francisco Bay and the rest of California tended to 
have finer sediments, higher Total Organic Carbon, higher concentrations of sediment 
nitrogen and phosphorus, and higher average Effects Range-Median Quotient (ERM-Q) 
values than estuarine intertidal areas in Washington and Oregon. Levels of sediment 
contamination West wide were low, with only 0.21% of the intertidal area of the West 
Coast estuaries having exceedances of >5 Effects Range Low (ERL) concentrations 
and 0.3% of the intertidal area exceeding Effects Range Median (ERM) concentrations. 

Average densities of benthic infauna were highest in Oregon, with California and 
San Francisco having lower but similar abundances, and Washington having the lowest 
value. The benthic community was dominated by polychaetes, oligochaetes and 
amphipods. Surprisingly, the single most abundant polychaete in the West Coast 
intertidal was the nonindigenous Manayunkia aestuarina, introduced from the Northeast 
Atlantic. San Francisco habitats other than the high marsh were the most invaded with 
an average of almost 50% of the classified species per sample consisting of 
nonindigenous species. Puget Sound samples contained about 26% nonindigenous 
species compared to 40% to 44% for coastal Oregon and Washington. 

Vegetation was present in the quadrats at 150 of the 217 sites sampled, and 
included 28 emergent macrophytes, 2 seagrasses, and macroalgal taxa. Eighty-two 
percent of macrophyte taxa occurred at three or fewer sites. The most frequently 
occurring emergent macrophyte taxa were marsh jaumea ( Jaumea carnosa) and 
pickleweed ( Salicornia virginica). The greatest numbesr of emergent macrophyte 
species were observed in California (n = 11), and in San Francisco Bay (n = 17) where 
high marsh was included in the study. Mean relative cover of nonindigenous emergent 
macrophyte species was low (8%) throughout the West. Mean cover by nonindigenous 
species was highest in Washington (21%), where both salt marsh cordgrass Spartina 
alterniflora and the introduced seagrass Zostera japonica were found. No 


58 



nonindigenous macrophyte species were observed at California sites, except one high 
marsh site in San Francisco Bay. 

The results of this assessment study represent the first regional scale survey of 
the condition of intertidal wetland habitats on the West Coast. Findings confirm results 
from previous National Coastal Assessment studies of West Coast estuaries that have 
indicated sediment contamination issues are limited in extent, but that West Coast 
estuaries have been broadly invaded by nonindigenous species. Further refinement of 
measurement approaches for plant community and shoreline development indicators 
are needed. 


59 


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Carlton, J.T. 1996. Biological invasions and cryptogenic species. Ecology 77:1653- 
1654. 

Chapman, J. W. and J. A. Dorman. 1975. Diagnosis, systematics and notes on 

Grandidierella japonica (Amphipoda: Gammaridea) and its introduction to the 
Pacific coast of the United States. Bulletin of the Southern California Academy of 
Sciences 74:104-108. 

Cohen, A. and J.T. Carlton. 1995. Nonindigenous aquatic species in a United States 
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and Wildlife Service, Washington, D.C. Report No. PB 96-166525. 

Comeleo, R.L., J.F. Paul, P.V. August, J. Copeland, C. Baker, S.S. Hale, and R.W. 
Latimer. 1996. Relationships between watershed stressors and sediment 
contamination in Chesapeake Bay estuaries. Landscape Ecology 11:307-319. 

Diaz-Ramos, S., D.L. Stevens, Jr., and A.R. Olsen. 1996. EMAP Statistics Methods 
Manual. EPA/620/R-96/002. Corvallis, OR: U.S. Environmental Protection 
Agency, Office of Research and Development, National Health and 
Environmental Effects Research Laboratory. 

Engle, V.D., J.K. Summers, and G.R. Gaston. 1994. A benthic index of environmental 
condition of Gulf of Mexico estuaries. Estuaries 17:372-384. 

Ferraro, S.P. and F.A. Cole. 2007. Benthic macrofauna-habitat associations in Willapa 
Bay, Washington, USA. Estuarine, Coastal and Shelf Science 71:491-507. 

Hayslip, G., L. Edmond, V. Partridge, W. Nelson, H. Lee, F. Cole, J. Lamberson, and L. 
Caton. 2006. Ecological Condition of the Estuaries of Oregon and Washington. 
EPA 910-R-06-001. U.S. Environmental Protection Agency, Office of 
Environmental Assessment, Region 10, Seattle, Washington. 

Hyland, J. L., T.J. Herrlinger, T.R. Snoots, A.H. Ring-wood, R.F. Van Dolah, C.T. 

Hackney, G.A. Nelson, J.S. Rosen, and S.A. Kokkinakis. 1996. Environmental 
Quality of Estuaries of the Carolinian Province: 1994. Annual Statistical Summary 
for the 1994 EMAP- Estuaries Demonstration Project in the Carolinian Province. 
NOAA Technical Memorandum NOS ORCA 97. NOAA/NOS, Office of Ocean 
Resources Conservation and Assessment, Silver Spring, MD. 102 p. 

Lauenstein, G.G. and A.Y. Cantillo (eds.). 1993. Sampling and analytical methods of the 
National Status and Trends Program National Benthic Surveillance and Mussel 
Watch Projects 1984-1992: Comprehensive descriptions of trace organic 
analytical methods, Volume IV NOAA Technical Memorandum NOS ORCA 71, 
Silver Spring, MD. 182 pp. 

Lauenstein, G.G., E.A. Crecelius, and A.Y. Cantillo. 2000. Baseline metal 

concentrations of the U.S. West Coast and their use in evaluating sediment 
contamination. Presented at 21st Ann. Soc. Environ. Toxicology and Chemistry 
meeting, November 12 - 15, 2000, Nashville Tennessee. 


60 


Lee II, H. and D.A. Reusser, with contributions from K. Welch, M. Ranelletti, L. 

Hillmann, and R. Fairey. 2007. Pacific Coast Ecosystem Information System 
(PCEIS). Version 1.2. (Georeferenced Access database developed by EPA and 
USGS). 

Lee II, H., B. Thompson, and S. Lowe. 2003. Estuarine and scalar patterns of invasion 
in the soft-bottom benthic communities of the San Francisco Estuary. Biological 
Invasions 5:85-102. 

Lee, H. II, C.A. Brown, B.L. Boese, and D.R. Young (eds.). 2006. Proposed 

Classification Scheme for Coastal Receiving Waters Based on SAV and Food 
Web Sensitivity to Nutrients, Volume 2: Nutrient Drivers, Seagrass Distributions, 
and Regional Classifications of Pacific Northwest Estuaries, United States 
Environmental Protection Agency Report, Office of Research and Development, 
National Health and Environmental Effects Laboratory. Internal Report. 

Llanso, R. J., L. C. Scott, J. L. Hyland, D. M. Dauer, D. E. Russell, and F. W. Kutz. 

2002. An Estuarine Benthic Index of Biotic Integrity for the Mid-Atlantic Region of 
the United States. II. Index Development. Estuaries 25:1231-1242. 

Long, E.D. and D.D. MacDonald. 1998. Recommended uses of empirically derived, 
sediment quality guidelines for marine and estuarine ecosystems. Human and 
Ecological Risk Assessment 4:1019-1093. 

Long, E.D., L.J. Field, and D.D. MacDonald. 1998.Predicting toxicity in marine 

sediments with numerical sediment quality guidelines. Environmental Toxicology 
and Chemistry 17:714-727. 

Long, E.R., D.D. MacDonald, S.L. Smith, and F.D. Callander. 1995. Incidence of 

adverse biological effects within ranges of chemical concentrations in marine and 
estuarine sediments. Environmental Management 19:81-97. 

Long, E.R., J. Hameedi, A. Robertson, M. Dutch, S. Aasen, K. Welch, S. Magoon, R. 
Carr, T. Johnson, J. Biedenbach, K. Scott, C. Mueller, and J. Anderson. 2000. 
Sediment Quality in Puget Sound. Year 2 - Central Puget Sound. National 
Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, 
MD. NOS NCCOS CCMA Technical Memo No. 147 , and Washington State 
Department of Ecology, Olympia, WA, Publication No. 00-03-055. 353 p. 

Neira, C., L.A. Levin, and E.D. Grosholz. 2005. Benthic macrofaunal communities of 
three sites in San Francisco Bay invaded by hybrid Spartina, with comparison to 
uninvaded habitats. Marine Ecology Progress Series 292:111-126. 

Nelson, W.G., H. Lee II, and J.O. Lamberson. 2005. Condition of Estuaries of California 
for 1999: A Statistical Summary. Office of Research and Development, National 
Health and Environmental Effects Research Laboratory, EPA 620/R-05/004. 

Nelson, W.G., H. Lee II, J.O. Lamberson, V. Engle, L. Harwell, and L.M. Smith. 2004. 
Condition of Estuaries of Western United States for 1999: A Statistical Summary. 
Office of Research and Development, National Health and Environmental Effects 
Research Laboratory, EPA/620/R-04/200. 

Nelson, W.G.; R. Brock, H. Lee II,J.O. Lamberson, and F.A. Cole. 2007. Condition of 
Estuaries and Bays of Hawaii for 2002: A Statistical Summary. Office of 


61 


Research and Development, National Health and Environmental Effects 
Research Laboratory, EPA/620-R-07/001. 

Rodiguez, W., P.V. August, Y. Wang, J.F. Paul, A. Gold, and N. Rubenstein. 2007. 
Empirical relationships between land use/cover and estuarine condition in the 
Northeastern United States. Landscape Ecology 22:403-417. 

Strobel, C. J., H. W. Buffum, S.J. Benyi, E.A. Petrocelli, D.R. Reifsteck, and D.J. Keith. 
1995. Statistical summary: EMAP - Estuaries Virginian Province - 1990 to 1993. 
U.S. EPA National Health and Environmental Effects Research Laboratory, 
Atlantic Ecology Division, Narragansett, R.l. EPA/620/R-94/026. 72 p. plus 
Appendices A-C. 

Summers, J.K., J.M. Macauley, P.T. Heitmuller, V.D. Engle, A.M. Adams, and G.T. 
Brooks. 1993. Annual Statistical Summary: EMAP-Estuaries Louisianian 
Province -1991. U.S. Environmental Protection Agency, Office of Research and 
Development, Environmental Research Laboratory, Gulf Breeze, FL. EPA/600/R- 
93/001. 101 p. plus Appendices A-C. 

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contamination in the San Francisco estuary, California, USA. Environmental 
Toxicology and Chemistry 23:2178-2187. 

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Assessment Program (EMAP): Laboratory Methods Manual - Estuaries, Volume 
1: Biological and physical analyses. Office of Research and Development, 
Environmental Monitoring and Systems Laboratory, Cincinnati, OH. EPA/600/4- 
91/024. 321-324. 

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U.S. EPA (U.S. Environmental Protection Agency). 2004. National Coastal Condition 
Report II. EPA-620/R-03/002. U.S. Environmental Protection Agency, Office of 
Research and Development and Office of Water, Washington, D.C. 286 p. 
Available at: http://www.epa.qov/nccr/2005/downloads.html 

U.S. EPA (U.S. Environmental Protection Agency). 2006. National Estuary Program 
Coastal Condition Report. EPA-842/B-06/001. U.S. Environmental Protection 
Agency, Office of Water, Washington, D.C. 445 p. Available at: 
http://www.epa.gov/owow/oceans/nepccr/index.html 

U.S. General Accounting Office (GAO). 2000. Water Quality - EPA and State Decisions 
Limited by Inconsistent and Incomplete Data. Report to the Chairman, 
Subcommittee on Water Resources and Environment, Committee on 
Transportation and Infrastructure, House of Representatives. Report GAO/RCED 
00-54. 78 p. 

Wilson, S. and V. Partridge. 2007. Condition of Outer Coastal Estuaries of Washington 
State, 1999. A Statistical Summary. Publication No. 07-03-012. Washington 
State Department of Ecology, Olympia, WA 249 p. 


62 





Appendix Table 1.1. Summary of quality assurance results for sediment metals. RPD = relative percent difference of 
duplicate samples. CV = coefficient of variation. 


RPDs and CVs 
of matrix spikes 
and reference 
materials <30%? 

Yes 

Yes 

Yes 

Recovery of 
matrix spikes 
within 50%- 
120%? 

Yes 

Yes 

Yes 

70% of 
analytes 
within ±35% 
of true 
value? 

Yes 

Yes 

Yes 

% of 
analytes 
within ±35% 
of true value 

100% 

93% 

100% 

Average % 
deviation from 
reference 
material within 
±20% of true 
value 

Yes 

Yes 

Yes 

Average % 
deviation from 
true value of 
reference 
material 
(# Analytes) 

7% (15) 

15% (15) 

4% (13) 

State 

California 

Oregon 

Washington 


0 

O 

c 

0 

L_ 

0 

it 

~o 

c 

0 

o 

L. 

0 

CL 

0 

> 

JO 

0 

l_ 

II 

D 

CL 

X 

< 

Q_ 

c 

0 

E 

'~a 
0 
c t ,> 

i_ 

o 

<-»— 

0 

3 

CO 

0 

k_ 

0 

o 

c . 
03 C 

3.2 

8 .2 

>% > 


TO u 

-I 

M— 

o O 
>%it 

TO o 

E o 
E ii 
13 > 


co 

csi 

0 

n 

TO 


O 

CO 

_0 

Cl 

E 

TO 

CO 

0 


TO 

O 


X 

TD 
C 
0 
Q- Cl 

< 'D 


RPDs and CVs 

of matrix spikes 

and reference 

materials <30%? 

No (33%) 

No (34%) 

Yes 

Recovery of 

matrix spikes 

within 50%- 

120%? 

Yes 

Yes 

Yes 

70% of 
analytes 
within ±35% 
of true 
value? 

Yes 

No 

Yes 

%of 
analytes 
within ±35% 
of true value 

100% 

53% 

74% 

Average % 
deviation from 
reference 
material within 
±30% of true 
value 

Yes 

No 

No 

Average % 
deviation from 
true value of 
reference 
material 
(# Analytes) 

16% (12) 

43% (22) 

32% (19) 

State 

California 

Oregon 

Washington 


m 






















CD 

O 

c 

CD 

i— 

0 

s= 


c 

0 

o 

l_ 

0 

CL 

0 

> 

JD 

0 


Q 

CL 

QC 

co 

CD 

O 

CL 

c 

0 

E 

TJ 

0 

0 

£ 

0 

3 

0 

0 

i_ 

0 

O 

c 

0 c 
d.2 

8 .g 

a CD 
>% > 

0 ° 

-I 

< 4 — 

o .2 

0 o 
E o 


CO 


> 

o 


RPDs and CVs 
of matrix spikes 
and reference 
materials <30%? 

No non-zero 
replicates 

No (49%) 

Yes 

Recovery of 
matrix spikes 
within 50%- 
120%? 

Yes 

Yes 

Yes 

70% of 
analytes 
within ±35% 
of true 
value? 

Yes 

No 

No 

%of 
analytes 
within ±35% 
of true value 

100% 

00 

CO 

67% 

Average % 
deviation 
from 

reference 
material 
within ±30% 
of true value 

Yes 

No 

No 

Average % 
deviation from 
true value of 
reference 
material 
(# Analytes) 

15% (14) 

146% (21) 

32% (18) 

State 

California 

Oregon 

Washington 


■o 

0 


0 

o 

o 

-C 

o 


II 

O 
CL 
QC 

0 
0 
-g 5 

g 0 

0 0 

Q. N 

"O 0 
0 _Q 

0 2 
.2 o 

1 ^ 
■f= 03 
o X 

i— 0 

0 _C 
£ M 

° CD 

cO 
0 x 

0 . 
I— c 
Q .2 
Q 0 

0 > 

3 ° 

8 g 


— 0) c 

0 O 
=5 CD O) 
cr ^ 0 

o §-6 

>>-G 0 

I ■5 5 

= 0 <= 
o 
c 

CO 0 0 

• 0 o 5 

^ y= 2 


E 

0 


0 


RPDs and CVs 

of matrix spikes 

and reference 

materials <30%? 

No non-zero 

replicates 

Yes 

Yes 

Recovery of 

matrix spikes 

within 50%- 

120%? 

Yes (19 

analytes) 

Yes 

Yes 

70% of 
analytes 
within ±35% 
of true 
value? 

Yes (only 2 

analytes) 

No 

Yes 

%of 
analytes 
within ±35% 
of true value 

100% 

50% 

100% 

Average % 
deviation 
from 

reference 
material 
within ±30% 
of true value 

Yes (only 2 
analytes) 

No 

Yes 

Average % 
deviation from 
true value of 
reference 
material 
(# Analytes) 

13% (2) 

127% (8) 

57% (w/o HCB) 

24% (7) 

State 

California 

Oregon 

Washington 


^r 

vo 
























Appendix Table 2. Sampling coordinates for the 2002 West Coast Intertidal 
Assessment. The Area Weight represents the total estuarine area within a multidensity 
category divided by the number of samples obtained in that category. 


EMAP 
Station ID 

Location 

Latitude 

Longitude 

Multidensity 

Category 

Area 

Weight 

WA02-0002 

Willapa Bay 

46.58 

-123.93 

Willa 

7.74 

WA02-0003 

Willapa Bay 

46.49 

-124.03 

Willa 

7.74 

WA02-0004 

Port Orchard 

47.70 

-122.56 

Puget 

13.97 

WA02-0005 

Grays Harbor 

46.97 

-124.02 

Washi 

23.16 

WA02-0006 

Case Inlet 

47.10 

-122.71 

Puget 

13.97 

WA02-0007 

Willapa Bay 

46.52 

-123.93 

Willa 

7.74 

WA02-0010 

Oyster Bay 

47.11 

-123.07 

Puget 

13.97 

WA02-0011 

Willapa Bay 

46.67 

-123.93 

Willa 

7.74 

WA02-0012 

Drayton Passage 

47.23 

-122.72 

Puget 

13.97 

WA02-0014 

Port Susan 

48.12 

-122.42 

Puget 

13.97 

WA02-0016 

Skagit Bay 

48.33 

-122.46 

Puget 

13.97 

WA02-0017 

Willapa Bay 

46.42 

-123.98 

Willa 

7.74 

WA02-0018 

Willapa Bay 

46.72 

-123.91 

Willa 

7.74 

WA02-0019 

Willapa Bay 

46.68 

-123.96 

Willa 

7.74 

WA02-0020 

Case Inlet 

47.35 

-122.80 

Puget 

13.97 

WA02-0021 

Grays Harbor 

47.02 

-124.10 

Washi 

23.16 

WA02-0022 

Port Gardner 

48.03 

-122.26 

Puget 

13.97 

WA02-0023 

Willapa Bay 

46.51 

-123.96 

Willa 

7.74 

WA02-0024 

Lummi Bay 

48.77 

-122.66 

Puget 

13.97 

WA02-0025 

Grays Harbor 

46.99 

-124.08 

Washi 

23.16 

WA02-0026 

Grays Harbor 

46.96 

-123.97 

Washi 

23.16 

WA02-0027 

Willapa Bay 

46.49 

-124.03 

Willa 

7.74 

WA02-0028 

Port Orchard 

47.67 

-122.56 

Puget 

13.97 

WA02-0032 

Skagit Bay 

48.37 

-122.53 

Puget 

13.97 

WA02-0035 

Willapa Bay 

46.64 

-123.96 

Willa 

7.74 

WA02-0036 

Lynch Cove 

47.43 

-122.87 

Puget 

13.97 

WA02-0037 

Grays Harbor 

47.04 

-124.08 

Washi 

23.16 

WA02-0039 

Willapa Bay 

46.49 

-123.95 

Willa 

7.74 

WA02-0040 

Samish Bay 

48.56 

-122.47 

Puget 

13.97 

WA02-0041 

Grays Harbor 

46.99 

-124.13 

Washi 

23.16 

WA02-0043 

Willapa Bay 

46.63 

-124.05 

Willa 

7.74 

WA02-0044 

Peale Passage 

47.22 

-122.91 

Puget 

13.97 

WA02-0045 

Grays Harbor 

46.88 

-124.07 

Washi 

23.16 

WA02-0046 

Skagit Bay 

48.29 

-122.42 

Puget 

13.97 

WA02-0048 

Skagit Bay 

48.33 

-122.45 

Puget 

13.97 

WA02-0049 

Naselle River 

46.44 

-123.92 

Willa 

7.74 

WA02-0050 

Willapa Bay 

46.73 

-123.89 

Willa 

7.74 

WA02-0051 

Willapa Bay 

46.66 

-123.97 

Willa 

7.74 

WA02-0052 

Carr Inlet 

47.39 

-122.63 

Puget 

13.97 

WA02-0054 

Port Susan 

48.19 

-122.39 

Puget 

13.97 


65 



















WA02-0056 

Skagit Bay 

48.34 

-122.50 

Puget 


13.97 

WA02-0059 

Willapa Bay 

46.46 

-123.99 

Willa 


7.74 

WA02-0060 

Drayton Harbor 

48.97 

-122.76 

Puget 


13.97 

WA02-0061 

Willapa Bay 

46.72 

-123.97 

Willa 


7.74 

WA02-0062 

Lilliwaup Creek 

47.48 

-123.08 

Puget 


13.97 

WA02-0064 

Swinomish Cannel 

48.44 

-122.50 

Puget 


13.97 

WA02-0065 

Willapa Bay 

46.41 

-124.00 

Willa 


7.74 

WA02-0066 

Willapa River 

46.68 

-123.82 

Willa 


7.74 

WA02-0067 

Willapa Bay 

46.60 

-123.95 

Willa 


7.74 

WA02-0068 

Thorndike Bay 

47.78 

-122.79 

Puget 


13.97 

WA02-0070 

Willapa Bay 

46.53 

-123.91 

Willa 


7.74 

WA02-0071 

Willapa Bay 

46.71 

-123.93 

Willa 


7.74 

WA02-0072 

Duckabush River 

47.64 

-122.92 

Puget 


13.97 

WA02-0075 

Willapa Bay 

46.46 

-124.00 

Willa 


7.74 

WA02-0078 

Willapa Bay 

46.73 

-123.90 

Willa 


7.74 

WA02-0087 

Palix River 

46.63 

-123.93 

Willa 


7.74 

WA02-0091 

Willapa Bay 

46.48 

-123.96 

Willa 


7.74 

WA02-0102 

Willapa Bay 

46.59 

-123.94 

Willa 


7.74 

WA02-0123 

Willapa Bay 

46.52 

-123.98 

Willa 


7.74 

WA02-0127 

Willapa Bay 

46.49 

-123.99 

Willa 


7.74 

WA02-0143 

Willapa Bay 

46.67 

-123.98 

Willa 


7.74 

OR02-0001 

Nehalem Bay 

45.69 

-123.90 

Orego 


2.18 

OR02-0002 

Coos Bay 

43.45 

-124.20 

Coosb 


0.89 

OR02-0003 

Siletz Bay 

44.90 

-124.02 

Orego 


2.18 

OR02-0004 

Coos Bay 

43.39 

-124.21 

Coosb 


0.89 

OR02-0005 

Tillamook Bay 

45.53 

-123.92 

Orego 


2.18 

OR02-0006 

Coos Bay 

43.41 

-124.20 

Coosb 


0.89 

OR02-0007 

Yaquina Bay 

44.60 

-124.02 

Orego 


2.18 

OR02-0009 

Tillamook Bay 

45.51 

-123.90 

Orego 


2.18 

OR02-0010 

Coos Bay 

43.43 

-124.22 

Coosb 


0.89 

OR02-0011 

Siuslaw River 

43.97 

-124.06 

Orego 


2.18 

OR02-0012 

Umpqua River 

43.72 

-124.10 

Orego 


2.18 

OR02-0013 

Netarts Bay 

45.40 

-123.94 

Orego 


2.18 

OR02-0014 

Coos Bay 

43.42 

-124.28 

Coosb 


0.89 

OR02-0015 

Netarts Bay 

45.41 

-123.95 

Orego 


2.18 

OR02-0016 

Coos Bay 

43.34 

-124.32 

Coosb 


0.89 

OR02-0018 

Coos Bay 

43.42 

-124.24 

Coosb 


0.89 

OR02-0019 

Yaquina Bay 

44.62 

-124.01 

Orego 


2.18 

OR02-0020 

Coos Bay 

43.37 

-124.17 

Coosb 


0.89 

OR02-0021 

Sixes River 

42.85 

-124.54 

Orego 


2.18 

OR02-0022 

Coos Bay 

43.42 

-124.21 

Coosb 


0.89 

OR02-0023 

Yaquina Bay 

44.61 

-124.02 

Orego 


2.18 

OR02-0024 

Coos Bay 

43.33 

-124.32 

Coosb 


0.89 

OR02-0026 

Coos Bay 

43.41 

-124.23 

Coosb 


0.89 

OR02-0027 

Alsea Bay 

44.45 

-124.05 

Orego 


2.18 

OR02-0028 

Coos Bay 

43.28 

-124.23 

Coosb 


0.89 


66 




OR02-0029 

Sand Lake 

45.28 

-123.96 

Orego 

2.18 

OR02-0030 

Coos Bay 

43.39 

-124.19 

Coosb 

0.89 

OR02-0031 

Coos Bay 

43.47 

-124.20 

Coosb 

0.89 

OR02-0032 

Umpqua River 

43.74 

-124.16 

Orego 

2.18 

OR02-0033 

Tillamook Bay 

45.53 

-123.90 

Orego 

2.18 

OR02-0034 

Coos Bay 

43.39 

-124.30 

Coosb 

0.89 

OR02-0035 

Siletz Bay 

44.89 

-124.01 

Orego 

2.18 

OR02-0036 

Coos Bay 

43.39 

-124.19 

Coosb 

0.89 

OR02-0038 

Coos Bay 

43.43 

-124.21 

Coosb 

0.89 

OR02-0039 

Yaquina River 

44.57 

-124.01 

Orego 

2.18 

OR02-0041 

Tillamook Bay 

45.51 

-123.94 

Orego 

2.18 

OR02-0042 

Coos Bay 

43.37 

-124.21 

Coosb 

0.89 

OR02-0043 

Alsea River 

44.42 

-124.02 

Orego 

2.18 

OR02-0044 

Coos Bay 

43.32 

-124.20 

Coosb 

0.89 

OR02-0045 

Sand Lake 

45.29 

-123.94 

Orego 

2.18 

OR02-0046 

Coos Bay 

43.38 

-124.19 

Coosb 

0.89 

OR02-0047 

Netarts Bay 

45.38 

-123.96 

Orego 

2.18 

OR02-0048 

Coquille River 

43.13 

-124.41 

Orego 

2.18 

OR02-0049 

Tillamook Bay 

45.52 

-123.93 

Orego 

2.18 

OR02-0050 

Coos Bay 

43.45 

-124.23 

Coosb 

0.89 

OR02-0051 

Siuslaw River 

43.98 

-124.08 

Orego 

2.18 

OR02-0052 

Umpqua River 

43.72 

-124.15 

Orego 

2.18 

OR02-0053 

Netarts Bay 

45.38 

-123.95 

Orego 

2.18 

OR02-0054 

Coos Bay 

43.42 

-124.19 

Coosb 

0.89 

OR02-0055 

Tillamook Bay 

45.49 

-123.90 

Orego 

2.18 

OR02-0056 

Coos Bay 

43.33 

-124.31 

Coosb 

0.89 

OR02-0057 

Tillamook Bay 

45.50 

-123.89 

Orego 

2.18 

OR02-0058 

Coos Bay 

43.40 

-124.21 

Coosb 

0.89 

OR02-0059 

Alsea Bay 

44.43 

-124.04 

Orego 

2.18 

OR02-0061 

Salmon River 

45.03 

-123.98 

Orego 

2.18 

OR02-0062 

Coos Bay 

43.39 

-124.20 

Coosb 

0.89 

OR02-0063 

Coos Bay 

43.45 

-124.22 

Coosb 

0.89 

OR02-0064 

Umpqua River 

43.72 

-124.16 

Orego 

2.18 

OR02-0066 

Neawanna Creek 

46.00 

-123.92 

Orego 

2.18 

OR02-0067 

Coos Bay 

43.45 

-124.21 

Coosb 

0.89 

OR02-0068 

Nestucca Bay 

45.18 

-123.94 

Orego 

2.18 

OR02-0069 

Coos Bay 

43.39 

-124.20 

Coosb 

0.89 

OR02-0070 

Tillamook Bay 

45.48 

-123.89 

Orego 

2.18 

OR02-0071 

Coos Bay 

43.40 

-124.21 

Coosb 

0.89 

OR02-0072 

Alsea Bay 

44.44 

-124.05 

Orego 

2.18 

OR02-0073 

Coos Bay 

43.35 

-124.31 

Coosb 

0.89 

CA02-0001 

Eel River 

40.66 

-124.29 

Calif 

2.04 

CA02-0002 

Morro Bay 

35.33 

-120.84 

Calif 

2.04 

CA02-0003 

Drakes Bay 

38.04 

-122.93 

Calif 

2.04 

CA02-0004 

Areata Bay 

40.84 

-124.08 

Calif 

2.04 

CA02-0006 

Tomales Bay 

38.23 

-122.96 

Calif 

2.04 


67 







































































































































CA02-0007 

Areata Bay 

40.80 

-124.12 

Calif 

2.04 

CA02-0008 

Areata Bay 

40.85 

-124.11 

Calif 

2.04 

CA02-0009 

Elkhorn Slough 

36.83 

-121.74 

Calif 

2.04 

CA02-0010 

Areata Bay 

40.88 

-124.14 

Calif 

2.04 

CA02-0011 

Tomales Bay 

38.12 

-122.86 

Calif 

2.04 

CA02-0012 

Humboldt Bay 

40.70 

-124.22 

Calif 

2.04 

CA02-0013 

Areata Bay 

40.85 

-124.09 

Calif 

2.04 

CA02-0014 

Elkhorn Slough 

36.83 

-121.75 

Calif 

2.04 

CA02-0015 

Areata Bay 

40.86 

-124.16 

Calif 

2.04 

CA02-0016 

Drakes Estero 

38.05 

-122.94 

Calif 

2.04 

CA02-0019 

Areata Bay 

40.85 

-124.15 

Calif 

2.04 

CA02-0020 

Drakes Bay 

38.08 

-122.83 

Calif 

2.04 

CA02-0021 

Chorro Creek 

35.34 

-120.83 

Calif 

2.04 

CA02-0022 

Humboldt Bay 

40.69 

-124.23 

Calif 

2.04 

CA02-0023 

Areata Bay 

40.84 

-124.10 

Calif 

2.04 

CA02-0024 

Corte Madera Creek 

37.92 

-122.68 

Calif 

2.04 

CA02-0025 

Areata Bay 

40.82 

-124.15 

Calif 

2.04 

CA02-0026 

Bodega Harbor 

38.33 

-123.05 

Calif 

2.04 

CA02-0027 

Areata Bay 

40.82 

-124.12 

Calif 

2.04 

CA02-0028 

Areata Bay 

40.85 

-124.11 

Calif 

2.04 

CA02-0029 

Areata Bay 

40.83 

-124.17 

Calif 

2.04 

CA02-0030 

Smith River (CA) 

41.94 

-124.20 

Calif 

2.04 

CA02-0031 

Chorro Creek 

35.35 

-120.84 

Calif 

2.04 

CA02-0032 

Tomales Bay 

38.09 

-122.83 

Calif 

2.04 

CA02-0033 

Areata Bay 

40.83 

-124.17 

Calif 

2.04 

CA02-0301 

Atascadero Creek 

34.42 

-119.84 

Bight 

0.55 

CA02-0302 

Huntington Harbour 

33.70 

-118.05 

Bight 

0.55 

CA02-0303 

Point Mugu Lagoon 

34.12 

-119.15 

Bight 

0.55 

CA02-0304 

Huntington Harbour 

33.69 

-118.04 

Bight 

0.55 

CA02-0305 

Sweetwater River 

32.64 

-117.11 

Bight 

0.55 

CA02-0306 

Point Mugu Lagoon 

34.11 

-119.14 

Bight 

0.55 

CA02-0307 

Newport Bay 

33.65 

-117.88 

Bight 

0.55 

CA02-0308 

Point Mugu Lagoon 

34.11 

-119.09 

Bight 

0.55 

CA02-0309 

Huntington Harbour 

33.73 

-118.07 

Bight 

0.55 

CA02-0311 

Point Mugu Lagoon 

34.10 

-119.12 

Bight 

0.55 

CA02-0312 

Newport Bay 

33.63 

-117.89 

Bight 

0.55 

CA02-0313 

Marina Del Rey 

33.97 

-118.45 

Bight 

0.55 

CA02-0314 

Anaheim Bay 

33.74 

-118.08 

Bight 

0.55 

CA02-0315 

San Diego River 

32.77 

-117.25 

Bight 

0.55 

CA02-0316 

Point Mugu Lagoon 

34.11 

-119.11 

Bight 

0.55 

CA02-0317 

Tijuana River 

32.56 

-117.12 

Bight 

0.55 

CA02-0318 

Santa Ana River 

33.64 

-117.97 

Bight 

0.55 

CA02-0319 

Carpinteria Creek 

34.40 

-119.54 

Bight 

0.55 

CA02-0320 

Anaheim Bay 

33.74 

-118.09 

Bight 

0.55 

CA02-0323 

Atascadero Creek 

34.42 

-119.84 

Bight 

0.55 

CA02-0324 

Anaheim Bay 

33.75 

-118.08 

Bight 

0.55 


68 














































CA02-0325 

*- : - 

Point Mugu Lagoon 

34.11 

-119.13 

Bight 

0.55 

CA02-0326 

Huntington Harbour 

33.74 

-118.08 

Bight 

0.55 

CA02-0327 

San Diego Bay 

32.61 

-117.11 

Bight 

0.55 

CA02-0328 

Point Mugu Lagoon 

34.11 

-119.12 

Bight 

0.55 

CA02-0329 

Tijuana River 

32.57 

-117.12 

Bight 

0.55 

CA02-0333 

Huntington Harbour 

33.74 

-118.08 

Bight 

0.55 

CA02-0334 

Point Mugu Lagoon 

34.11 

-119.11 

Bight 

0.55 

CA02-0343 

Atascadero Creek 

34.42 

-119.88 

Bight 

0.55 

CA02-0352 

San Elijo Lagoon 

33.01 

-117.27 

Bight 

0.55 

CA02-0601 

SF Bay - Coyote Creek 

37.47 

-122.04 

SF High Marsh 

4.50 

CA02-0602 

SF Bay -Dutchman Slough 

38.05 

-122.13 

SF Flat 

13.12 

CA02-0603 

SF Bay - San Leandro Creek 

37.67 

-122.17 

SF Flat 

13.12 

CA02-0604 

SF Bay - Petaluma River 

38.21 

-122.57 

SF Low Marsh 

2.28 

CA02-0605 

SF Bay - Redwood Creek 

37.51 

-122.22 

SF Low Marsh 

2.28 

CA02-0606 

SF Bay - Dutchman Slough 

38.14 

-122.37 

SF High Marsh 

4.50 

CA02-0607 

SF Bay - Dutchman Slough 

38.16 

-122.39 

SF High Marsh 

4.50 

CA02-0608 

SF Bay - Napa River 

38.05 

-122.07 

SF Low Marsh 

2.28 

CA02-0609 

SF Bay - Mud Slough 

37.48 

-121.97 

SF High Marsh 

4.50 

CA02-0611 

SF Bay - Newark SF Bay - 
Slough 

37.50 

-122.09 

SF Flat 

13.12 

CA02-0612 

SF Bay - Gallinas Creek 

38.01 

-122.49 

SF High Marsh 

4.50 

CA02-0613 

SF Bay - Redwood Creek 

37.51 

-122.17 

SF Flat 

13.12 

CA02-0615 

SF Bay - Napa River 

38.10 

-122.09 

SF High Marsh 

4.50 

CA02-0616 

SF Bay - Suisun Bay 

38.06 

-121.90 

SF High Marsh 

4.50 

CA02-0617 

SF Bay - Coyote Creek 

37.45 

-122.07 

SF Flat 

13.12 

CA02-0618 

SF Bay - San Rafael Bay 

37.98 

-122.38 

SF Flat 

13.12 

CA02-0619 

SF Bay - Coyote Hills Slough 

37.54 

-122.11 

SF High Marsh 

4.50 

CA02-0620 

SF Bay - Petaluma River 

38.14 

-122.52 

SF High Marsh 

4.50 

CA02-0621 

SF Bay - Redwood Creek 

37.52 

-122.21 

SF Low Marsh 

2.28 

CA02-0622 

SF Bay - Dutchman Slough 

38.15 

-122.32 

SF Low Marsh 

2.28 

CA02-0623 

SF Bay - Montezuma Slough 

38.15 

-121.92 

SF Low Marsh 

2.28 


SF Bay - Outer Oakland 





CA02-0624 

Harbor 

37.83 

-122.32 

SF Flat 

13.12 

CA02-0625 

SF Bay - Steinberger Slough 

37.54 

-122.22 

SF Low Marsh 

2.28 

CA02-0626 

SF Bay - Dutchman Slough 

38.11 

-122.33 

SF Flat 

<N 

CO 

CA02-0628 

SF Bay - Corte Madera Creek 

37.93 

-122.51 

SF High Marsh 

4.50 

CA02-0629 

SF Bay - San Francisco Bay 

37.64 

-122.15 

SF Low Marsh 

2.28 

CA02-0630 

SF Bay - Petaluma River 

38.09 

-122.48 

SF Flat 

13.12 

CA02-0632 

SF Bay - Napa River 

38.12 

-122.07 

SF Low Marsh 

2.28 

CA02-0634 

SF Bay - Dutchman Slough 

38.16 

-122.40 

SF High Marsh 

4.50 

CA02-0635 

SF Bay - Steinberger Slough 

37.54 

-122.23 

SF High Marsh 

4.50 


69 
















































































































































































































Appendix Table 3. Summary of sediment composition (percent fines), total organic 
carbon (TOC), total nitrogen (TN) and total phosphorus (TP) concentrations, and 
contaminant concentrations for all intertidal sites, including high marsh, sampled in 
2002. ERL count and ERM count are the number of exceedances of ERL and ERM, 
respectively. * Number of analytes that exceed Effects Range Low (ERL) guidelines 
(Long et al., 1995). n/a = not available for this station. 


Characteristics Contaminants 


EMAP 
Station ID 

Percent 

Fines 

Total 

Organic 

Carbon 

Total 

Nitrogen 

Total 

Phosphorus 

ERMQ 

Metals* 

PAHs* 

Pest* 

PCBs* 

ERL 

Count 

ERM 

Count 

CA02-0001 

94.0 

2.1 

0.21 

0.07 

0.065 

2 

2 



4 

0 

CA02-0002 

89.0 

1.8 

0.23 

0.07 

0.058 

2 




2 

0 

CA02-0003 

13.0 

0.3 

0.04 

0.03 

0.013 





0 

0 

CA02-0004 

4.0 

10.9 

0.89 

0.13 

0.058 

2 




2 

0 

CA02-0006 

5.0 

0.4 

0.06 

0.06 

0.015 




0 

0 

CA02-0007 

90.0 

2.3 

0.28 

0.08 

0.058 

2 

1 



3 

0 

CA02-0008 

94.0 

1.6 

0.21 

0.09 

0.063 

3 

1 



4 

0 

CA02-0009 

n/a 

8.7 

0.84 

0.10 

0.049 

2 




2 

0 

CA02-0010 

72.0 

6.4 

0.53 

0.03 

0.066 

3 




3 

0 

CA02-0011 

10.0 

0.3 

0.04 

0.08 

0.041 

2 

1 



3 

0 

CA02-0012 

88.0 

1.5 

0.21 

0.09 

0.050 

1 

1 



2 

0 

CA02-0013 

90.0 

2.1 

0.27 

0.09 

0.056 

2 

1 



3 

0 

CA02-0014 

75.0 

7.3 

0.75 

0.09 

0.049 

2 




2 

0 

CA02-0015 

83.0 

1.6 

0.21 

0.02 

0.053 

2 

1 


3 

0 

CA02-0016 

6.0 

0.3 

0.05 

0.09 

0.013 





0 

0 

CA02-0019 

86.0 

1.8 

0.24 

0.08 

0.058 

3 

1 



4 

0 

CA02-0020 

27.0 

10.9 

0.87 

0.08 

0.057 

2 




2 

0 

CA02-0021 

92.0 

4.4 

0.39 

0.06 

0.065 

2 




2 

0 

CA02-0022 

90.0 

2.0 

0.27 

0.06 

0.054 

2 




2 

0 

CA02-0023 

92.0 

1.5 

0.18 

0.04 

0.062 

3 

1 



4 

0 

CA02-0024 

24.0 

1.0 

0.14 

0.06 

0.027 

1 




1 

0 

CA02-0025 

72.0 

1.0 

0.12 

0.07 

0.049 

1 

1 



2 

0 

CA02-0026 

17.0 

0.7 

0.12 

0.07 

0.021 





0 

0 

CA02-0027 

89.0 

1.1 

0.13 

0.04 

0.055 

1 

1 



2 

0 

CA02-0028 

93.0 

1.6 

0.19 

0.11 

0.065 

3 

1 



4 

0 

CA02-0029 

89.0 

1.5 

0.19 

0.07 

0.055 

2 

1 



3 

0 

CA02-0030 

6.0 

0.2 

0.03 

0.10 

0.046 

1 




1 

0 

CA02-0031 

83.0 

7.1 

0.61 

0.17 

0.070 

2 




2 

0 

CA02-0032 

85.0 

1.3 

0.16 

0.07 

0.042 

1 




1 

0 

CA02-0033 

92.0 

2.7 

0.37 

0.11 

0.058 

3 

1 



4 

0 

CA02-0301 

93.0 

2.7 

0.23 

0.18 

0.048 

3 




3 

0 

CA02-0302 

22.0 

1.0 

0.12 

0.05 

0.070 

1 


2 


3 

0 


70 















CA02-0303 

49.0 

7.5 

0.65 

0.09 

0.036 

1 


1 

0 

CA02-0304 

51.0 

8.6 

0.86 

0.10 

0.092 

5 


5 

0 

CA02-0305 

91.0 

2.0 

0.19 

0.17 

0.045 

2 


2 

0 

CA02-0306 

72.0 

6.9 

0.60 

0.12 

0.357 

3 

2 

5 

2 

CA02-0307 

77.0 

9.5 

0.65 

0.20 

0.143 

3 

2 

.T.". 

5 

1 

CA02-0308 

62.0 

8.1 

0.71 

0.06 

0.164 

3 

2 

5 

1 

CA02-0309 

71.0 

6.8 

0.66 

0.13 

0.065 

4 


4 

0 

CA02-0311 

19.0 

18.0 

2.30 

0.17 

0.042 

i 


1 

0 

CA02-0312 

74.0 

1.2 

0.17 

0.02 

0.101 

3 

2 

5 

0 

CA02-0313 

82.0 

3.1 

0.38 

0.08 

0.121 

6 


6 

0 

CA02-0314 

72.0 

9.8 

0.89 

0.07 

0.129 

4 

2 

6 

0 

CA02-0315 

4.0 

0.0 

0.00 

0.06 

0.005 



0 

0 


CA02-0316 21.0 

CA02-0317 81.0 

CA02-0318 36.0 

CA02-0319 33.0 

CA02-0320 80.0 

CA02-0321 75.0 
CA02-0323 99.0 

CA02-0324 52.0 

CA02-0325 47.0 

CA02-0326 69.0 

CA02-0327 29.0 

CA02-0328 85.0 

CA02-0329 22.0 

CA02-0333 29.0 

CA02-0334 18.0 
CA02-0343 73.0 

CA02-0352 40.0 

CA02-0601 46.0 

CA02-0602 94.0 

CA02-0603 10.0 

CA02-0604 83.0 

CA02-0605 40.0 

CA02-0606 55.0 

CA02-0607 69.0 

CA02-0608 36.0 

CA02-0609 87.0 

CA02-0611 90.0 
CA02-0612 62.0 

CA02-0613 67.0 

CA02-0615 31.0 

CA02-0616 40.0 

CA02-0617 91.0 

CA02-0618 13.0 


0.3 

1.6 

0.6 

2.1 

3.4 
0.9 
1.9 
1.8 

2.5 

7.1 

1.9 

3.1 

15.5 
16.0 

21.4 
0.9 

8.5 
8.7 

1.2 
0.2 

4.6 

2.6 

7.2 

4.9 
13.8 
2.6 
1.0 

3.3 

1.9 

11.4 
11.6 
1.1 
0.5 


0.03 

0.19 

0.06 

0.18 

0.37 

0.10 

0.19 

0.18 

0.25 

0.81 

0.13 

0.31 

1.22 

1.54 

1.45 

0.12 

1.29 

0.81 

0.13 

0.03 

0.40 

0.41 

0.50 

0.41 

0.98 

0.26 

0.14 

0.31 

0.19 

0.89 

0.80 

0.14 

0.07 


0.09 

0.10 

0.03 

0.17 

0.08 

0.06 

0.11 


0.03 

0.16 

0.16 

0.12 

0.13 

0.08 

0.14 

0.12 

0.06 

0.09 

0.07 

0.11 

0.09 

0.14 

0.11 

0.07 

0.07 

0.07 

0.11 

0.08 

0.07 

0.04 

0.13 

0.07 

0.17 

0.10 


0.011 

0.070 

0.070 

0.032 

0.056 

n/a 

0.066 

0.033 

0.027 

0.068 

0.021 

0.130 

0.045 

0.049 

0.219 

0.040 

0.052 

0.084 

0.069 

0.025 

0.072 

0.084 

0.078 

0.059 

0.082 

0.078 

0.079 

0.087 

0.079 


0.108 


0.064 

0.083 


1 

3 

4 
2 
2 
2 
2 
2 

5 
3 


4 

5 
4 

4 

5 
3 

3 

5 
2 

6 

4 
3 


2 

2 


0 

5 

2 

0 

3 

n/a 

4 
0 
1 
3 




0 

6 

2 

2 


0.025 


4 
2 
2 

5 

3 
0 

4 

5 
4 

4 

5 
3 
3 
5 

3 
7 

4 
4 
0 


0 

0 

0 

0 


0 

n/a 

0 

0 

0 

0 

0 

0 

0 

0 

2 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 


0 

0 

0 


0 

0 

0 

0 


71 






























































































































CA02-0619 

61.0 

7.9 

0.73 

0.11 

0.076 

4 


! ! 

4 

0 

CA02-0620 

67.0 

2.6 

0.24 

0.02 

0.059 

4 



4 

0 

CA02-0621 

46.0 

16.2 

1.36 

0.09 

0.082 

3 

1 


4 

0 

CA02-0622 

56.0 

4.1 

0.37 

0.06 

0.076 

4 



4 

0 

CA02-0623 

42.0 

13.0 

0.81 

0.10 

0.068 

4 



4 

0 

CA02-0624 

10.0 

0.5 

0.06 

0.08 

0.021 

1 



1 

0 

CA02-0625 

64.0 

3.1 

0.36 

0.06 

0.070 

2 



2 

0 

CA02-0626 

97.0 

0.8 

0.10 

0.09 

0.067 

3 


|.|. 

3 

0 

CA02-0628 

34.0 

12.3 

0.94 

0.09 

0.101 

4 



4 

0 

CA02-0629 

79.0 

3.0 

0.29 

0.10 

0.059 

1 



1 

0 

CA02-0630 

96.0 

1.0 

0.13 

0.02 

0.078 

3 



3 

0 

CA02-0632 

30.0 

7.5 

0.63 

0.07 

0.058 

4 



4 

0 

CA02-0634 

52.0 

6.6 

0.52 

0.02 

0.046 

2 



2 

0 

CA02-0635 

64.0 

3.0 

0.40 

0.03 

0.065 

3 



3 

0 

OR02-0001 

41.7 

2.2 

0.19 

0.06 

0.034 

1 



1 

0 

OR02-0002 

67.5 

1.5 

0.15 

0.07 

0.035 

2 



2 

0 

OR02-0003 

22.4 

1.2 

0.11 

0.07 

0.032 

1 



1 

0 

OR02-0004 

40.3 

1.7 

0.13 

0.05 

0.023 



0 

0 

OR02-0005 

6.2 

0.3 

0.03 

0.04 

0.017 



0 

0 

OR02-0006 

51.7 

1.4 

0.14 

0.06 

0.030 

1 



1 

0 

OR02-0007 

46.3 

4.3 

0.40 

0.10 

0.027 



0 

0 

OR02-0009 

9.4 

0.3 

0.04 

0.08 

0.048 

2 



2 

0 

OR02-0010 

11.1 

0.4 

0.05 

0.05 

0.022 



0 

0 

OR02-0011 

22.7 

1.5 

0.13 

0.04 

0.017 



0 

0 

OR02-0012 

73.7 

2.9 

0.26 

0.06 

0.033 

1 



1 

0 

OR02-0013 

16.4 

0.9 

0.08 

0.04 

0.019 



0 

0 

OR02-0014 

1.2 

0.1 

0.01 

0.01 

0.006 



0 

0 

OR02-0015 

5.2 

0.4 

0.05 

0.03 

0.017 



0 

0 

OR02-0016 

16.0 

0.4 

0.04 

0.02 

0.027 

1 



1 

0 

OR02-0018 

45.4 

2.1 

0.69 

0.04 

0.029 



0 

0 

OR02-0019 

48.4 

1.6 

0.16 

0.06 

0.026 

1 



1 

0 

OR02-0020 

48.8 

2.4 

0.80 

0.08 

0.029 

1 



1 

0 

OR02-0021 

9.5 

0.7 

0.47 

0.03 

0.040 

1 



1 

0 

OR02-0022 

15.0 

0.6 

0.06 

0.03 

0.011 



0 

0 

OR02-0023 

56.6 

2.4 

0.22 

0.07 

0.030 

1 



1 

0 

OR02-0024 

25.9 

1.4 

0.11 

0.04 

0.021 



0 

0 

OR02-0026 

64.8 

2.7 

0.22 

0.05 

0.105 

1 


1 

2 

1 

OR02-0027 

20.3 

0.5 

0.05 

0.04 

0.016 



0 

0 

OR02-0028 

71.2 

5.1 

0.35 

0.09 

0.041 

2 



2 

0 

OR02-0029 

0.9 

0.0 

0.01 

0.01 

0.018 

1 



1 

0 

OR02-0030 

28.3 

1.1 

0.50 

0.04 

0.020 



0 

0 

OR02-0031 

87.2 

2.0 

0.19 

0.08 

0.036 

2 



2 

0 

OR02-0032 

11.1 

0.5 

0.46 

0.03 

0.024 

1 



1 

0 

OR02-0033 

19.8 

0.7 

0.07 

0.05 

0.021 



0 

0 

OR02-0034 

64.5 

5.4 

0.51 

0.08 

0.025 

1 



1 

0 


72 









































































































































OR02-0035 

64.9 

2.7 

0.22 

0.08 

0.037 

2 


2 

0 

OR02-0036 

18.3 

1.0 

0.09 

0.03 

0.014 



0 

0 

OR02-0038 

25.1 

0.7 

0.07 

0.05 

0.024 



0 

0 

OR02-0039 

83.4 

2.8 

0.28 

0.10 

0.036 

1 


1 

0 

OR02-0041 

00 

o 

0.2 

0.02 

0.03 

0.010 



0 

0 

OR02-0042 

22.9 

1.2 

0.08 

0.03 

0.021 



0 

0 

OR02-0043 

36.2 

1.7 

0.15 

0.07 

0.024 



0 

0 

OR02-0044 

70.4 

4.0 

1.16 

0.06 

0.088 

1 

2 

3 

0 

OR02-0045 

25.1 

1.5 

0.18 

0.08 

0.020 

1 


1 

0 

OR02-0046 

7.4 

0.3 

0.03 

0.02 

0.012 



o 

0 

OR02-0047 

42.8 

1.2 

0.57 

0.05 

0.023 

1 


1 

0 

OR02-0048 

1.7 

0.1 

0.02 

n/a 

0.009 



0 

0 

OR02-0049 

16.3 

0.5 

0.05 

0.04 

0.014 



0 

0 

OR02-0050 

55.5 

1.5 

0.12 

0.05 

0.030 

1 


1 

0 

OR02-0051 

36.9 

1.6 

0.15 

0.06 

0.022 



0 

0 

OR02-0052 

47.0 

1.1 

0.09 

0.04 

0.031 

1 


1 

0 

OR02-0053 

39.8 

1.3 

0.54 

0.04 

0.021 

j 


0 

0 

OR02-0054 

33.5 

1.1 

0.57 

0.04 

0.026 

1 


1 

0 

OR02-0055 

3.5 

0.3 

0.05 

0.08 

0.040 

2 


2 

0 

OR02-0056 

83.4 

1.3 

0.13 

0.05 

0.031 

1 


1 

0 

0 

OR02-0057 

13.1 

0.5 

0.04 

0.07 

0.061 

2 

2 

OR02-0058 

23.5 

1.2 

0.07 

0.04 

0.024 



o 

0 

OR02-0059 

17.5 

0.5 

0.06 

0.04 

0.016 



0 

0 

OR02-0061 

70.2 

2.1 

0.68 

0.06 

0.041 

2 


2 

0 

OR02-0062 

8.9 

0.3 

0.04 

0.02 

0.013 



0 

0 

OR02-0063 

41.3 

1.3 

0.10 

0.04 

0.025 

1 


1 

0 

OR02-0064 

15.3 

0.6 

0.07 

0.03 

0.014 



0 

0 

OR02-0066 

46.7 

3.9 

0.36 

0.12 

0.020 

1 


1 

0 

OR02-0067 

36.1 

1.4 

0.62 

0.03 

0.027 



0 

0 

OR02-0068 

4.8 

0.3 

0.17 

0.02 

0.017 

1 


1 

0 

OR02-0069 

12.4 

1.0 

0.07 

0.03 

0.016 



0 

0 

OR02-0070 

84.7 

3.9 

0.77 

0.10 

0.041 

2 


2 

0 

OR02-0071 

14.5 

0.7 

0.39 

0.02 

0.014 



0 

0 

OR02-0072 

9.6 

0.6 

0.50 

0.04 

0.022 



0 

0 

OR02-0073 

0.7 

0.1 

0.09 

0.02 

0.008 



0 

0 

WA02-0002 

3.6 

0.2 

0.03 

0.02 

0.017 



0 

0 

WA02-0003 

74.4 

2.2 

0.22 

0.07 

0.039 

1 


1 

0 

WA02-0004 

6.1 

0.1 

0.02 

0.02 

0.012 



0 

0 

WA02-0005 

7.8 

0.3 

0.04 

0.03 

0.017 



0 

0 

WA02-0006 

95.2 

0.6 

0.05 

0.06 

0.025 



0 

0 

WA02-0007 

CD 

00 

—i 

1.6 

0.14 

0.07 

0.037 



0 

0 


WA02-0010 91.7 2.4 0.26 0.10 0.051 2 2 0 

WA02-0011 72.8 1.3 0.14 0.06 0.033 0 0 

WA02-0012 2.2 0.0 0.01 0.02 0.019 1 1 0 

WA02-0014 2.0 0.0 0.01 0.04 0.018 1 1 0 


73 





















































































































































































WA02-0016 

2.6 


0.2 

0.02 

0.05 

0.019 

0 

0 

WA02-0017 

66.5 


1.6 

0.16 

0.07 

0.036 

1 1 

0 

WA02-0018 

4.4 


0.3 

0.03 

0.03 

0.020 

0 

0 

WA02-0019 

4.1 


0.1 

0.02 

0.03 

0.015 

0 

0 

WA02-0020 

1.9 


0.0 

0.01 

0.03 

0.016 

0 

0 

WA02-0021 

8.0 


0.2 

0.03 

0.03 

0.018 

0 

0 

WA02-0022 

2.2 


0.2 

0.02 

0.04 

0.023 

1 1 

0 

WA02-0023 

26.7 


0.7 

0.07 

0.05 

0.021 

0 

0 

WA02-0024 

12.2 


0.4 

0.05 

0.04 

0.018 

0 

0 

WA02-0025 

22.2 


0.6 

0.07 

0.04 

0.022 

0 

0 

WA02-0026 

11.9 


0.3 

0.04 

0.03 

0.044 

2 2 

0 

WA02-0027 

40.1 


1.2 

0.10 

0.06 

0.029 

0 

0 

WA02-0028 

9.6 


0.2 

0.03 

0.03 

0.017 

0 

0 

WA02-0032 

5.3 


0.1 

0.02 

0.05 

0.021 

0 

0 

WA02-0035 

13.0 


0.5 

0.06 

0.04 

0.018 

0 

0 

WA02-0036 

5.1 


0.4 

0.03 

0.03 

0.021 

0 

0 

WA02-0037 

72.2 


1.4 

0.13 

0.06 

0.050 

2 2 

0 

WA02-0039 

87.0 


3.0 

0.27 

0.09 

0.041 

1 1 

0 

WA02-0040 

33.6 


0.6 

0.08 

0.07 

0.025 

0 

0 

WA02-0041 

7.7 


0.3 

0.04 

0.03 

0.017 

0 

0 

WA02-0043 

17.3 


0.6 

0.07 

0.08 

0.019 

0 

0 

WA02-0044 

4.2 


1.2 

0.10 

0.03 

0.022 

1 1 

0 

WA02-0045 

21.4 


0.8 

0.07 

0.04 

0.025 

0 

0 

WA02-0046 

3.3 


0.0 

0.01 

0.06 

0.026 

1 1 

0 

WA02-0048 

3.9 


0.1 

0.03 

0.06 

0.024 

0 

0 

WA02-0049 

58.6 


1.9 

0.16 

0.08 

0.042 

1 1 

0 

WA02-0050 

62.8 


1.3 

0.11 

0.05 

0.032 

0 

0 

WA02-0051 

2.9 


0.1 

0.02 

0.03 

0.013 

0 

0 

WA02-0052 

15.7 


0.7 

0.06 

0.02 

0.015 

0 

0 

WA02-0054 

8.1 


0.2 

0.03 

0.05 

0.035 

1 1 

0 

WA02-0056 

5.2 


0.1 

0.02 

0.04 

0.020 

0 

0 

WA02-0059 

74.8 


2.1 

0.20 

0.08 

0.037 

1 1 

0 

WA02-0060 

40.5 


1.2 

0.13 

0.05 

0.031 

0 

0 

WA02-0061 

11.2 


0.4 

0.04 

0.04 

0.018 

0 

0 

WA02-0062 

0.6 


0.3 

0.03 

0.04 

0.029 

2 2 

0 

WA02-0064 

39.2 


0.6 

0.06 

0.06 

0.030 

0 

0 

WA02-0065 

2.3 


0.0 

0.01 

0.03 

0.013 

0 

0 

WA02-0066 

80.0 


2.2 

0.19 

0.06 

0.042 

0 

0 

WA02-0067 

3.0 


0.1 

0.02 

0.02 

0.015 

0 

0 

WA02-0068 

4.6 


0.2 

0.03 

0.03 

0.018 

0 

0 

WA02-0070 

56.1 


2.0 

0.14 

0.06 

0.040 

0 

0 

WA02-0071 

23.8 


0.9 

0.08 

0.05 

0.026 

0 

0 

WA02-0072 

4.2 


0.3 

0.05 

0.05 

0.028 

2 2 

0 

WA02-0075 

1.8 


0.2 

0.02 

0.02 

0.017 

0 

0 

WA02-0078 

63.6 


1.7 

0.14 

0.05 

0.035 

0 

0 


74 

































































































































WA02-0087 

64.5 

1.2 

0.13 

0.05 

0.039 

1 




1 

0 

WA02-0091 

73.1 

3.1 

0.28 

0.11 

0.042 

1 




1 

0 

WA02-0102 

3.7 

0.2 

0.03 

0.02 

0.015 





0 

0 

WA02-0123 

6.9 

0.2 

0.03 

0.04 

0.016 





0 

0 

WA02-0127 

14.8 

0.5 

0.05 

0.03 

0.019 





0 

0 

WA02-0143 

2.8 

0.0 

0.02 

0.03 

0.014 





0 

0 

















Total 

282 

19 

23 0 

324 

7 


75 



































































Appendix Table 4. Vegetation type (EM = emergent macrophyte, SE = seagrass, AG = algae) and class (NIS = 
nonindigenous species) for all species encountered and frequency of occurrence in quadrats and transects. West = all 
sites except for San Francisco high marsh. CA = all California sites except for San Francisco Bay. 



VO 

r- 







r~- 

r-~ 





Appendix Table 5. Relative percent cover of vegetation taxa (mean and range at sites present) in quadrats. West = all 
sites except for San Francisco high marsh. CA = all California sites except for San Francisco Bay. 


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Brown algae 8 1-22 - - - - 12 3-22 1 1-1 

Red algae 1 M . - . . 12 3-22 1 1-1 

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Zostera marina 71 14-122 ... - 56 14-122 84 29-119 





Appendix Table 7. Quadrat biomass (g/m 2 ) of vegetation taxa (mean and range at sites present). West = all sites except 
for San Francisco high marsh. CA = all California sites except for San Francisco Bay. 


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Artemisia douglasiana 

Atriplex triangularis 

Batis maritima 

Carex lyngbyei 

Cotula coronopifolia 

Cordylanthus maritimus ssp palustris 

Cuscuta salina 

Distichlis spicata 

Eleocharis palustris 

Eleocharis parvula 

Euthamia occidentalis 

Frankenia salina 

Grindelia stricta 

Jaumea carnosa 

Juncus gerardii 

Lepidium latifolium 

Limonium californicum 

Polygonum lapathifolium 

Rosa californica 

Salicornia bigelovii 

Salicornia virginica 

Scirpus acutus 

Scirpus americanus 

Scirpus maritimus 

Scirpus robustus 

Spartina alterniflora 

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Green algae 

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Environmental Protection 
Agency 


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Washington, DC 20460 


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